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European University Viadrina Frankfurt (Oder)

Faculty of Social and Cultural Sciences

Master Thesis

“Assessing the Perception of Workplace Diversity. A Case Study on Diversity Climate at CERN.”

Supervisor:

Prof. Dr. Jacek Sójka Dr. Marcin Poprawski

Author: Kristin Kaltenhäuser

Matrikel: 84674

Zu den Schafweiden 13 99098 Erfurt

Phone: +49 176 96369956

Email: kristin.kaltenhauser@gmail.com

Erfurt, 18 July 2016

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Table of Contents

1 Introduction ......................................................................................................................................... 2 

2 Literature review ................................................................................................................................. 4 

2.1 Diversity in the workforce ............................................................................................................ 4 

2.2 Effects of workplace diversity ...................................................................................................... 6 

2.3 Managing diversity: Diversity initiatives and training .................................................................. 8 

2.4 Diversity climate ........................................................................................................................ 12 

3 The organisation CERN .................................................................................................................... 15 

3.1 General facts ............................................................................................................................. 15 

3.2 Diversity at CERN ..................................................................................................................... 16 

4 Methodology ..................................................................................................................................... 21 

4.1 ODNA – The instrument ............................................................................................................ 21 

4.2 Adaptations to the CERN context ............................................................................................. 26 

4.3 Procedure .................................................................................................................................. 27 

4.4 The sample ............................................................................................................................... 27 

4.5 Method of analysis .................................................................................................................... 31 

5 Data analysis .................................................................................................................................... 33 

5.1 Descriptive statistics and correlations of the subscales ............................................................ 33 

5.2 Test of preconditions for statistical analysis .............................................................................. 35 

5.3 Test of hypotheses .................................................................................................................... 36 

5.3.1 Results for eight dimensions: H1 Gender .......................................................................... 37 

5.3.2 Results for eight dimensions: H2 Nationality ..................................................................... 43 

5.3.3 Results for eight dimensions: H3 Managerial responsibilities ........................................... 47 

5.3.4 Results for eight dimensions: H4 Generation (Age) .......................................................... 50 

5.3.5 Results for eight dimensions: H5 CERN Status ................................................................ 54 

5.3.6 Summary of the results ...................................................................................................... 60 

6 Discussion and recommendations ................................................................................................... 63 

7 Discussion of methodology .............................................................................................................. 65 

8 Tables and figures ............................................................................................................................ 67 

9 References ....................................................................................................................................... 72 

ANNEX 1 – Map of CERN Member States as of March 2016 ............................................................ 77 

ANNEX 2 – Actions Points of CERN Diversity Programme ................................................................ 78 

ANNEX 3 – The original ODNA ........................................................................................................... 79 

ANNEX 4 – Questionnaire introduction text ........................................................................................ 82 

ANNEX 5 – The Questionnaire – CERN version................................................................................. 83 

ANNEX 6 – Cronbach’s alpha for all eight dimensions ....................................................................... 88 

ANNEX 7 – Results ............................................................................................................................. 89 

Declaration of Originality ................................................................................................................... 104 

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1 Introduction

“In the twentieth century, ecologists and agriculturalists developed an increasingly so-phisticated understanding of the value of biological diversity, specifically the resilience

and adaptability it brings to ecosystems. In the twenty-first century, the ecosystem model has been applied to human systems, particularly to understand how organisa-

tions are structured and how they operate.” (Kreitz 2008: 2)

Diversity has become a popular slogan for organisations in the 21st century. Many

companies use its promotion to attract customers, but also talent and a positive pub-

licity. Yet few employers have succeeded in implementing successful and effective

diversity management initiatives. Many agree that the management of diversity is im-

portant, but fail to put in place effective and impactful measures to manage a diverse

workforce. Educating and training employees in a diverse work setting has experi-

enced a rise in popularity and a rise in offers by experts all around the world. How-

ever, the basis of the implementation of a successful measure is the assessment of

the present situation.

Tschirhart and Wise (2000) suggest that such an assessment should entail the use

of existing research on the topic and eliciting of employees’ perception: “Studies with

implications for the practice of managing for diversity must focus on relationships

among workers with varying levels of heterogeneity.” (ibid.: 387)

This study will bring together research, employee perceptions and an inspection of

existing measures for a case study of the international organisation CERN, based in

Geneva, Switzerland. The goal will be to assess the diversity climate of the organisa-

tion, to serve as a basis for recommendations on effective and targeted diversity train-

ing initiatives to increase productivity and efficiency. The term diversity climate entails

attitudes of members of personnel towards diversity, their perception of the attitude

of people around them and how the organisation is perceived to support and manage

a diverse workforce.

The assessment will build on research that exists in this area. There is much research

that has been carried out in the area of workforce diversity, but there is no research

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on workforce diversity in International Organisations. This is a unique setting, be-

cause these organisations are by definition culturally diverse, recruiting internationally

based on their setup.

A quantitative methodology approach was implemented to achieve the objective of

this research. The Organisational Needs Analysis (ODNA) developed by Prof. Molly

Dahm in 2009 was utilized as the data collection instrument. The instrument was de-

veloped to conduct a training needs analysis in organisations with a diverse work-

force. Social and psychological concepts are introduced and explained to interpret

the results of the data analysis.

Statistical analysis was carried out with the data collected with the ODNA to test the

following hypotheses:

H1 There is a difference in the diversity perspectives based on gender.

H2 There is a difference in the diversity perspectives based on nationality.

H3 There is a difference in the diversity perspectives based on level of managerial

responsibilities.

H4 There is a difference in the diversity perspectives based on generations.

H5 There is a difference in the diversity perspectives based on status at the organi-

sation.

The thesis is divided into six parts: The first part will give an overview over key re-

search and concepts in the areas of workforce diversity, its effects on an individual,

team and organisational level, as well as findings regarding the management of a

diverse workforce and the construct of diversity climate.

The second section will introduce CERN as an organisation and the setting of the

empirical research. Afterwards the methodology is explained and how it measures

the diversity climate of an organisation in general, as well as its adaptation to the

CERN context. The results of the data analysis are presented in chapter 5. The last

part will be a discussion of the results, as well as recommendations to the organisa-

tion and an evaluation of the methodology to explain its constraints.

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2 Literature review

The following chapters will introduce the basic social and psychological concepts that

contribute to understanding dynamics of a diverse workforce, and summarize rele-

vant research on the topic of workforce diversity. Due to the popularity of the subject

in practice as well as the academic world, there is an extensive list of related research.

For the purpose of this study, the focus is initially on the term of diversity and social

dynamics in a diverse workforce. Afterwards literature reflecting the effect of a diverse

workforce on an individual, as well as group and organisational level will be reviewed,

followed by an assessment of recommended frameworks of managing diversity. The

last part of the literature review entails an examination of the implications of the con-

cept of diversity climate.

2.1 Diversity in the workforce

To understand the different perceptions that individuals have towards diversity in their

work environment, a first step is to give an overview of the different ways to define

the term.

The concept of diversity is an evolving one, since it has emerged in the business

context in the 1980s. Schneider and Northcraft (1999) note that in today’s business

world but also in research on the topic, people refer to different types of workforce

diversity. Many researchers and organisations use a vague definition to cover a broad

range of obvious and hidden qualities of an individual, such as Wentling and Palma-

Rivas (1998), who state: “Diversity is all the ways in which we differ,” (ibid.: 241).

Others prefer a more practicable approach to the term when used in the business

context and analyse diversity in terms of social category membership. Thus people

are assigned to social groups based on a shared characteristic. Organisational diver-

sity initiatives often base these groups on functional demographic traits which are

directly relevant to organisational performance, such as gender, age, ethnicity etc.

(Schneider, Northcraft 1999).

In this study, the definition of Harrison et al. (2000) was adopted, who distinguish

between surface-level and deep-level diversity. Surface-level diversity is understood

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as differences in overt demographic characteristics, such as age, gender and ethnic-

ity. Harrison et al. note that not only organisations, but also individuals use these

characteristics to assign themselves and the people around them to groups, which

are ascribed certain attitudes and behaviors. These groups are often based on obvi-

ous demographic characteristics. The researchers found that individuals divide the

people they interact with into “in-groups”, with which they share traits they identify

with, as well as “out-groups”, which are social groups, they don’t identify with. In this

thesis, the term diversity, if not specified otherwise, connotes the various dimensions

of surface-level diversity.

Deep-level diversity on the other hand, refers to differences in psychological charac-

teristics, such as attitudes, personality, preferences and values. The paradigm of

deep-level diversity has begun to emerge in diversity research just recently and is

believed to be the basis of the effects of surface-level diversity, insofar as deep-level

traits are assumed to be the underlying motive for similarity-attraction (Byrne 1971)

and the definition of “in-groups”.

Harvey and Allard (2015) define the surface-level and deep-level dimensions of Har-

rison et al. according to their visibility: the dimensions of surface-level diversity are

the most visible and are primarily age, gender, race, mental and physical abilities,

ethnicity and sexual orientation. Harvey and Allard find them to be the more perma-

nent and less changeable, while most central to the in-group/out-group perception.

Whereas the deep-level dimensions are less visible.

This study focusses on surface-level diversity to assess the sample of members of

personnel at CERN. Cultural, age and gender diversity will be tested, as well as the

status of the individual in the organisation. Whereas the questions refer to surface-

level, as well as deep-level diversity, such as attitudes and values.

As broad as the definitions of diversity are, as much vary the methods to measure

and analyse it in an organisational context. Organisations and companies with a di-

verse workforce often track the demographics of their employees and compile the

data in a diversity report. Another measure of diversity aspects are surveys, as used

in this thesis. Konrad et al. (2006) note that the various ways of studying workplace

diversity provide scholars with different genres of workplace diversity research, which

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has to be taken into account when reviewing literature on the topic and using it as a

basis for further research.

One example of a potential erroneous assumption is the case of Allen et al. (2007).

They study the effect diversity has on organisational performance by surveying the

“perception of workplace diversity” (ibid.: 20). They therefore utilize the same term as

this thesis but describe it as the degree employees “perceive their workplace to be

diverse” (Allen et al. 2007: 22), contrary to the present paper which defines the per-

ception of workplace diversity as the openness towards and appreciation of diversity

(see chapter 2.4 on diversity climate).

2.2 Effects of workplace diversity

The focus of this study is the assessment of individual perceptions of the diversity

climate in an organisation and therefore from a social-psychological viewpoint. This

chapter will connect this individual level perspective to the performance of teams and

an organisation as a whole, by giving an overview of the effects of a diverse work-

force.

The questions raised in this paper are based on the notion that in a complex social

environment such as a diverse organisation, the individual forms and maintains its

identity by identifying with social groups. As mentioned in the previous chapter, re-

search suggests that in-groups and out-groups are defined by individuals based on

mostly overt demographic traits, such as culture, age, gender etc.

The theoretical premises of these finding are the well supported social identity theory

(Tajfel, Turner 1986) and the corresponding similarity-attraction paradigm (Byrne

1971). The two theories propose that individuals form their social identity by affiliating

to a social group in their immediate environment (in-groups), whereas they prefer to

affiliate with individuals they perceive to be similar to themselves based on surface-

level diversity groups. Several studies found that this affiliation has positive outcomes

on collaboration in teams who share characteristics: “interpersonal similarity in-

creases ease of communication, improves predictability of behaviour, and fosters re-

lationships of trust and reciprocity.” (MorBarak et al. 1998: 88, also: Hobman et al.

2004).

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As a result, in diverse organisations, where employees inevitably work with col-

leagues who are dissimilar, there are several theories suggesting that surface-level

diversity has a negative effect on the workforce due to the fact, that the individual

form unfavourable bias towards their out-groups: “Team members tend to have less

positive attitudes toward, and form fewer social attachments with those who are per-

ceived to be less like themselves” (Harrison et al. 2000: 5)

While the previously described research speaks about demographic traits and differ-

ences in general, there has been studies conducted featuring concrete surface-level

dimensions and specific performance outcomes of teams and the organisation as a

whole.

In the 1990s there were two opposing views emerging on whether a diverse workforce

has a generally positive or negative impact on performance. A group of organisational

scientists propose that team performance is enhanced by multiple perspectives of

people with different cultural backgrounds, gender and ages. Diversity is therefore

said to have positive effects on problem-solving, organisational flexibility and creativ-

ity based on the avoidance of a phenomenon called “groupthink”. This phenomenon

is defined as the absence of critical thinking in a homogeneous group due to the

preoccupation with maintaining the degree of cohesiveness in a group (Cox, Blake

1991). It was found that a certain degree of cultural diversity prevents this effect.

At the same time there was an opposing view, proving negative effects or none at all

of heterogeneous groups on team performance. Harrison et al. (2000) found that di-

versity has no benefit to team outcomes. Elvira and Cohen (2001) found a higher

turnover, as well as higher absenteeism, among employees of diverse workforces,

by examining personnel records of Fortune 500 companies. Jayne and Dipboye

(2004) and Tschirhart and Wise (2000) found by conducting empirical research on

collaboration in teams, effects such as less social integration of individuals, a lack of

team cohesion and greater communication problems. The studies suggest that these

negative effects occur with regard to several dimensions of surface-level diversity,

but mainly cultural, age and gender diversity.

In a fairly recent meta-analysis of research of the last 20 years on effects of a diverse

workforce on group performance by Joshi and Roh (2007), it was found that there are

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a fairly equal amount of studies concluding positive effects and of studies finding neg-

ative effects of a cultural, gender and age diverse group on performance. Tschirhart

and Wise (2000) furthermore propose that “We cannot claim that diversity has any

clear positive or negative effect on individual, group or organisational outcomes.”

(ibid.: 392)

In any case, most scholars defending the positive effects of a diverse workforce agree

that these are not achieved by hiring more cultural, age, and gender diverse employ-

ees alone: “Simply having a diverse workforce does not necessarily produce the pos-

itive outcomes that are often claimed by some of the more optimistic proponents.”

(Jayne, Dipboye 2004: 411). They underline the importance of managing a diverse

workforce in order to reap its benefits and avoid possible negative effects: “Workforce

social category diversity is not so much a benefit to have as it is a problem if avoided”

(Schneider, Northcraft 1999: 1450)

In an age of globalisation, there is an inevitable trend towards changing de-

mographics in the general population and therefore an increase in workforce diversity

for most companies and organisations. Therefore, paying attention to and managing

a diverse workforce is not only a concern of organisational performance but also a

matter of improving relationships with employees, who are becoming more diverse,

enhancing social responsibility, or at least avoiding legal conflicts, according to

Wentling and Palma-Rivas (1998: 242), who interviewed a group of diversity experts

in the American workforce,

2.3 Managing diversity: Diversity initiatives and training

This chapter will give a brief overview of the rationale behind diversity management

as well as a theoretical framework of diversity training efforts.

As shown, managing diversity is a strategic business issue for organisations in times

of globalisation. Historically, it evolved originally in the USA to provide a legally de-

fensive position against charges of discrimination, mainly in the form of affirmative-

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action programmes. However, in the 1990s diversity management emerged beyond

legal compliance: the premise became to not only recognize but leverage the benefits

of a diverse workforce described in the previous chapters, while avoiding possible

detriments. Managing diversity can be described as “an approach to fair treatment

that encourages employers to harness and value a wide range of visible differences

in their employees” (Foster, Harris 2005).

The starting point of every diversity initiative is as Digh (1998) states, that the man-

agement must “articulate, clearly and simply, what is meant by diversity and then

decide what approach to take. Does the organisation want to tolerate, celebrate,

value, manage, harness or leverage diversity?” (ibid.: 117).

There have been numerous studies on how to improve specifically Human Resource

practices to ensure fair processes throughout an organisation (e.g. Shen et al. 2009).

Cox (1994) suggests to address diversity on three levels: organisational, group and

individual level. All of them are tightly linked together, which can be explained with

the concept of organisational culture.

According to Ravasi and Schultz (2006) organisational culture is a set of shared as-

sumptions that guides what happens in an organisation by defining appropriate be-

haviors for various situations (ibid.). When managing diversity, these shared assump-

tions among employees need to be identified, analysed and addressed: “Managing

diversity means changing the culture - that is, the standard operating procedures. It

requires data, experimentation, and the discovery of the procedures that work best

for each group. It is more complex than conventional management but can result in

more effective organisations.” (Triandis et al. 1992: 773). Therefore, ensuring an in-

clusive organisational culture starts with a thorough assessment of needs, which

serve as a basis for the planning and building of targeted initiatives.

The assessment tool used in this study, the ODNA was developed to evaluate the

organisational culture and specifically the diversity climate of an organisation to be

utilised as a basis for developing successful diversity initiatives. The goal is to lay the

ground for giving recommendations on the areas to be targeted by diversity trainings

but also broader initiatives, by probing the individual perception of diversity in the

organisation. The underlying assumption here is that an impact on individual level,

will eventually lead to an impact on group as well as organisational level.

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Jayne and Dipboye (2004) warn, that there is no one-fits-all solution. Every organisa-

tion has its own delicacies that must be taken into account when developing diversity

initiatives. They argue however that good diversity programs have concrete goals and

action plans.

A common tool, and integral part of diversity management from its beginnings are

targeted diversity trainings. Ferdman and Brody (1996) conducted a comprehensive

analysis of diversity training models. They found that efforts can vary broadly in how

they are conceptualized and implemented, although most training initiatives focus on

domestic diversity and its implications for the workplace. The goals of training initia-

tives are often framed as either individual development and growth, or as a tool to

improve productivity.

When analysing the positioning of training initiatives in the timeline of an overall di-

versity effort, they identify two perspectives: Some scholars advocate to begin the

effort with educating employees and especially management. They reason that peo-

ple are drivers for change (ibid.: 295). Another group of researchers argue that a

change in attitude is a long-term process, which an organisation in today’s economy

cannot wait for. They point out that “behavioural changes will foster corresponding

changes in attitudes, rather than the other way around.” (ibid.) Thus it is believed that

system changes have to be made before emphasizing trainings. Both sides propose

valid arguments, however further research suggests that isolated diversity trainings

are less effective than a comprehensive diversity program that works on both fronts

(Paluck 2006: 585).

Ferdman and Brody propose four objectives for diversity training programs: The pro-

vision of knowledge and information, as well as the increase in awareness and un-

derstanding of differences are suggested to be a common goal among organisations.

Furthermore, the development of skills to bridge these differences, mainly through

communication training, is suggested as the necessary next step to have an impact

on the organisation’s diversity climate.

Successfully implemented trainings often feature two types of learning: didactic and

experiential learning. The basic premise of the didactic learning is that a reciprocal

understanding of other cultures is vital when it comes to interactions in a diverse

workplace. Its focus is to provide a knowledge base for trainees. Experiential learning

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on the other hand involves active participation and engagement as a mean to

strengthen intercultural sensitivity. According to Ferdman and Brody the tools of ex-

periential learning such as role plays and group discussions on the basis of personal

experiences, promote communication skills and affect attitudes, who can lead from

individual change to group and organisational change: “For many trainees, it is the

first time they realize that not everyone experiences the work environment in the

same way they do and that the variations are often connected to racial, ethnic and

gender identities.” (ibid.: 296)

There has been little reliable research conducted to measure diversity training suc-

cess. Studies either lack a sufficient sample size or miss the establishment of casual

effects of training components (Paluck 2006). The widely adopted assumption that

training will diminish the negative effects of a diverse workforce (as described in chap-

ter 2.2) and enforce the positive effects, such as a lower employee turnover, reduced

absenteeism and increased productivity (Dahm 2009, Larkey 1996) was never sup-

ported by properly conducted research.

One exception is a thorough study by Duguid and Thomas-Hunt (2015) who re-

searched the effect of raising awareness on stereotyping, such as unconscious bias.

Training on unconscious bias has become a very popular version of diversity training

within organisations across the US and Europe. It can be delivered in various ways

(e.g. e-learning, seminars and workshops), and aims to raise awareness to the fact,

that all people harbour implicit bias and to teach the trainees to be more mindful in

situations, where these might occur. Duguid and Thomas-Hunt’s findings point out

that unconscious bias awareness trainings can unintentionally encourage more bi-

ased thinking and behaviors among employees. They suggest that trainees feel less

motivated to change biases by hearing that others are biased and it’s ‘normal’ to hold

stereotypes.

Another problem is the transfer of training to the work situation. Since the training

context is different from the ongoing work context, it can be difficult for the trainees to

adapt the behaviors they learned in the training environment (Kossek et al. 2005: 63).

The review of the literature suggests, that more research is needed to assess the

positive effects of diversity training initiatives. When it comes to the most impactful

training concept, there is a lack of reliable research, but also the failure of training

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programs can be attributed to a lack of a suitable training needs assessment (Kirk-

patrick 1998). It is therefore essential to identify and address specific training targets

to enable a reliable assessment of training success. The assessment of the diversity

climate can result in recommendations on possible training targets. Depending on the

findings, alternative initiatives have to be taken into account to address the identified

issues.

2.4 Diversity climate

The diversity climate is part of the organisational culture, because it is as Cox (1994)

argues, determined by individual, group and organisational factors. “Diversity climate

refers to employee behaviors and attitudes that are grounded in perceptions of the

organisational context related to women and minorities” (MorBarak et al. 1998: 83).

The underlying assumption is, that employees’ behavior is driven by perceptions,

whether or not they are consistent with reality (Ensher et al. 2001: 53). This work

takes over this premise and therefore focusses on the assessment of the perceptions

of the employees and their openness towards and appreciation of the diversity in the

organisation.

Wentling and Palma-Rivas (1998) interviewed workforce diversity experts throughout

the US and found a consensus that the biggest barriers of leveraging the value of

diversity are the “negative attitudes to and the discomfort around people who are

different” (ibid.: 241). This can be due to the similarity-attraction paradigm, described

in chapter 2.2: people feel generally more comfortable around people who are similar

to them. Discomfort also comes from the widespread and often unconscious assump-

tion that approaches which differ from personal approaches are inferior. Kreitz (2008)

states that individuals prefer working in homogeneous groups and are prone to “avoid

and resist change” (Kreitz 2008: 4), which poses the main challenge for a positive

diversity climate in an organisation.

With regards to the social identity theory, which states that people create their social

identity by dividing the people around them in in- and out-groups (see chapter 2.1), a

strong diversity climate implies that the employees identify not only with groups based

on demographic characteristics, but simultaneously with their organisation. They dis-

play a dual identity (Hofhuis et al. 2011: 966).

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Kreitz (2008) argues that a goal of diversity management should be to change peo-

ple’s attitudes towards differences, and therefore how people interact. For this pur-

pose it is important to study and predict the range of interactions that occur in cultur-

ally diverse organisations and implement targeted communication and awareness

training initiatives.

This study is built on the assumption that surface-level diversity such as gender, age

and nationality determine the attitude towards diversity in the immediate (work) envi-

ronment. Research suggest e.g. that women have a more positive attitude towards

diversity than men (MorBarak et al. 1998). However, Sawyerr et al. (2005) found that

gender, race and age don’t generally determine the attitude towards differences, but

it’s more the underlying value structure of the individual. They found significant cor-

relations between value constructs such as openness to change, self-enhancement

and self-transcendence. Age, gender and race are likely to have a moderating effect

but don’t determine the attitude towards diversity generally. This implies that the

deep-level diversity determines attitudes towards diversity more severely than sur-

face-level diversity.

Kossek et al. (2005) found that individuals have more favourable attitudes towards

diversity initiatives when their work teams are more diverse, regardless of their own

demographics. Therefore, their attitudes towards organisational efforts to promote

cultural and gender diversity were more positive compared to other teams with less

diversity (ibid.: 60). They underline the importance to study to which extent employees

support an organisation’s pronounced value of diversity. The results can have impli-

cations on how future diversity initiatives are accepted.

It can be concluded that the diversity climate as well as the composition of the imme-

diate work team can predict the acceptance of diversity initiatives such as training.

Diversity training however is also aimed at improving the attitudes towards diversity

and the capability of individuals to work in a diverse team and leverage its benefits.

Cox (1994) argues that improvements in the diversity climate by introducing diversity

initiatives, enhances organisational effectiveness, measured by outcomes such as

productivity, quality, less turnover, better problem-solving and profitability.

14

One strategy to involve and engage employees early in the process, is assessing the

diversity climate. It is suggested to help to set the stage for future initiatives and give

the employees a chance to be involved in the design of them: “Assessments take into

consideration the experiences and attitudes of employees from different backgrounds

and signal to them that they are valued in the organisation.” (Cukier, Smarz 2012).

As demonstrated, research proposes the assessment of the diversity climate to early

identify possible conflicts or negative developments for the organisation. Further, data

collected over time, using the same instrument, can be used to evaluate the effec-

tiveness of organisational diversity initiatives. Kreitz (2008) calls for a systematic di-

versity climate assessment based on qualitative and quantitative research, because

it “studies root causes rather than symptoms” (ibid.:10). There are several tools avail-

able for practitioners to assess diversity, as well as diversity climate. Cukier and

Smarz (2012) compared and evaluated the most prominent tools in the US. They

conclude that every tool uses a different “diversity lens” (ibid.: 59), meaning the ap-

proaches to measuring the diversity climate in an organisation vary. The tool used in

this study, the ODNA was chosen because it is based on previous versions of as-

sessment tools, and an extensive review of literature on the topic. It will be further

explained in chapter 4.1.

Hofhuis et al. (2011) furthermore propose to include the attitude of the organisation

when studying the perception of diversity. They define the diversity climate as follows:

“Diversity climate is the degree to which an organisational climate facilitates the pres-

ence of cultural differences, and views this diversity climate as an asset.” (ibid.: 969).

This position is taken into account in chapter 3 of this thesis, where the organisation

CERN as the place where the study was carried out is described as well as its diver-

sity policy and training initiatives.

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3 The organisation CERN

The following chapter will give an overview of the organisational structure at CERN,

as well as the evolvement of diversity management at the organisation and the most

relevant recent diversity initiatives. It explains the organisation’s attitude towards di-

versity and gives a context to the empirical study, which is described in section 4 of

this thesis.

3.1 General facts

CERN, the European Organisation for Nuclear Research, is the world’s largest parti-

cle physics laboratory, based in Geneva, Switzerland. It has the status of an intergov-

ernmental organisation and is made up of 21 members states. The member states,

funding the organisation, are mostly European states and Israel, so far the only Non-

European state which was granted membership (for a map of all member states, see

Annex 1). CERN was founded in 1954 with the goal to provide and operate particle

accelerators and other infrastructure needed for high-energy physics research.

While the members of personnel (MPE) account for around 3000 of the CERN popu-

lation, there are an additional approximated 12 000 visiting scientists, associates and

users of the laboratory (MPA), who are using the CERN facilities1. For the purpose of

this study it is important to understand the population of the CERN site to grasp the

nature of its diversity. The MPEs are employed and paid by the research organisation.

They are sourced mainly from the member states, accounting for their financial con-

tribution to the organisation. The 12 000 MPAs of the laboratory are not employed by

CERN but sent by their home institutes. These collaborating institutes are mostly re-

search institutes and universities, which are located all over the world. Collaboration

agreements govern the relationship between the institutes and CERN and the dis-

patch of students and researchers, either full- or part-time, to carry out research at

the particle accelerators and other facilities at CERN.

1 http://cds.cern.ch/record/2154389/files/CERN-HR-STAFF-STAT-2015.pdf?version=1, access 07/0672016.

16

The organisation’s main purpose is to facilitate and carry out fundamental research

in the area of particle physics. CERN’s official mission statement also poses (1) the

advancement of technology and their impact on society, (2) the training of scientists

and engineers2 and (3) bringing nations together through science, as raison d’être of

its existence3.

The fact that CERN is by its constitution obliged to hire from all its 21 member states,

as well as the fostering of cross-cultural collaboration as part of its mission statement,

makes a culturally diverse workforce the premise.

3.2 Diversity at CERN

Diversity is embedded in the declared values of the organisation, as stated in the

CERN Code of Conduct: “CERN’s excellence derives from an environment in which

the knowledge and perspectives of a diverse workforce are valued and dialogue is

encouraged at all levels.”4

Organisational efforts to analyse and manage diversity at CERN go back to 1993

when an advisory group was created to reflect on the situation of women at CERN

and to address the gender imbalance in the organisation. This effort emerged into an

equal opportunity policy in 1996, as well as the appointment of an officer to enforce

this policy and the launch of a diversity programme in 20115.

The management and enhancement of gender diversity was therefore the starting

point and main focus of the diversity efforts in the organisation. The equal opportunity

policy from 1996 widens this scope and includes two other surface-level dimensions.

2 In accordance with this point, there are various student programmes at CERN, which are also rele-vant to this study. The Administrative and Technical student programme are aimed at undergraduate university students who spend up to 14 months at CERN during their studies as interns. A trainee is also an undergraduate intern at CERN. This programme is not tied to an official selection committee, as is the case for the Administrative and Technical student programme, and the internship cannot be longer than 6 months. The Doctoral student programme employs PhD students at CERN conducting their doctoral thesis in various fields. 3 http://jobs.web.cern.ch/content/our-mission, access: 07/06/2016. 4 http://jobs.web.cern.ch/content/culture-and-values, access: 07/06/2016. 5 More about the history of diversity at CERN: http://diversity.web.cern.ch/2015/03/equal-opportunities-diversity-1996-today.

17

It “rules out discrimination between members of its personnel on account of sex, race

or religion.” (Equal Opportunities Policy at CERN)6

The Diversity Programme launched in 2011 broadens the scope further. The CERN

diversity policy covers the following dimensions: gender, nationality/culture, profes-

sion, age/generation and individual differences7. Individual differences include ethnic

origin, sexual orientation, belief, disability, and opinions. It therefore takes into ac-

count surface-level as well as some deep-level diversity dimensions.

In 2008, before the launch of the diversity programme, the Equal Opportunities Office

carried out a survey among CERN staff members (MPE) The questionnaire had two

goals: “to spread awareness of equal opportunities at CERN”, as well as gather in-

sight into the issues CERN employees face in the context of diversity8. The question-

naire addressed the perception of harassment and discrimination at CERN, as well

as fair treatment in recruitment, career advancement and parental support. It also

investigated the knowledge of existing support structures and processes. Before the

launch of the Diversity Office, there were also interviews with employees, investigat-

ing expectations on the role of a diversity office, as well as general questions to in-

quire the perception of diversity support structures at CERN.

CERN therefore approached diversity management as described and recommended

in chapter 2.3 with collecting data before putting in place initiatives, with the benefit

of meeting assessed needs and involving employees in the diversity management

effort from the start. This is described in the CERN Diversity Policy:

“The Diversity Programme is monitored internally through surveys, interviews and

studies with in CERN with the aim of collecting input and feedback from both CERN

Management and CERN Contributors in order to continually adjust and align ac-

tions to the needs of the Organisation.” (CERN Diversity Policy, p. 5)9.

6 https://cds.cern.ch/record/1474077/files/1996_EOAPuk_leaflet.pdf, access 07/06/2016 (restricted access). 7 http://diversity.web.cern.ch/sites/diversity.web.cern.ch/files/DiversityPolicy.pdf, access, 07/06/2016. 8 Results of the Questionnaire on Equal Opportunities at CERN (2008). https://cds.cern.ch/rec-ord/1474082, access: 07/06/2016 (restricted access). 9 http://diversity.web.cern.ch/sites/diversity.web.cern.ch/files/DiversityPolicy.pdf, access, 07/06/2016.

18

However, the posed questions inquire broadly about fairness, discrimination and di-

versity management, without probing the understanding of these terms and the atti-

tude the employees have towards colleagues who are different.

Furthermore, a big part of the population at CERN, the 12 000 visiting scientists, user

and associates weren’t included in the survey. While it is true that many diversity

efforts are Human Resource activities, aimed at the individuals who are employed by

the organisation, the MPAs are a part of the organisation and influence the diversity

climate significantly. Therefore, they should be included in surveying the perception

of diversity at CERN.

The current activities of the Diversity Office can be tracked via the website of the

programme: http://diversity.web.cern.ch/. It shows that they are categorized into three

areas: recruitment, career development and work environment10. For the period from

2012 to 2015, there are seven strategic objectives defined, related to these areas and

with regard to the diversity dimensions (see Annex 2). For each objective there are

distinct actions. These actions imply an emphasis on addressing organisational pro-

cesses, in areas such as recruitment and career advancement, but also the provision

of support structures and the organisation of workshops and events to address an

inclusive work environment. The objectives as well as the CERN diversity website

imply that the topic of gender diversity is a main focus of the programme, which could

be explained by its historical evolvement from a working group addressing gender

imbalance at the organisation.

As mentioned in chapter 2.3, this thesis focusses on diversity competency trainings.

The following section will give a brief overview over the conducted trainings and

events, that can be seen as addressing an inclusive work environment and a positive

diversity climate.

Every half year CERN offers a diversity training that aims to “help to develop greater

sensitivity to differences and explore ways to recognise and overcome biases”11. The

half-day workshop involves group discussions and exercises, live audience surveys

10 http://diversity.web.cern.ch/framework/strategic-objectives, access 07/06/2016. 11 http://diversity.web.cern.ch/2016/05/diversity-action-workshop-7th-edition, access 07/06/2016.

19

and the provision of information on unconscious bias and diversity in general. It there-

fore features a mixture between experiential and didactic learning. The training is

offered for the whole CERN population, taking into account that all people on CERN

premises are part of an inclusive work environment. It is a non-mandatory training.

The goal of the workshop is framed as individual growth for the participants. As for

the objectives for diversity training as categorized by Ferdman and Brody (1996, see

chapter 2.3), the workshop aims to raise awareness, but also to develop skills, such

as dissecting and eliminating unconscious bias, when recognized.

Another training, that can be categorized as diversity training, are two full-day work-

shops on communication skills. This training is mandatory for all new staff members

at CERN since 2015, but open to the whole CERN population. It addresses commu-

nication skills, taking into account different personalities and different cultural com-

munication styles.

Furthermore, CERN offers a workshop which addresses gender inclusive writing in

the French language, offered by a language expert at CERN. This is a voluntary train-

ing aimed at writers in the CERN context, mainly administrative assistants and em-

ployees in the outreach and communication sections.

A last example of a training initiative at CERN, is a one-day workshop aimed at hiring

managers, to ensure a fair and competency based selection process at CERN. It is a

mandatory training, aimed at managers at CERN, who are about to be part of a se-

lection committee. Its goal is to prepare the participants for a structured selection

interview, that focusses on competencies, rather than subjectivity.

Furthermore, the Diversity Office has organized a number of talks and events to ad-

dress certain topics related to diversity.

While the former mentioned trainings involve both didactic as well as experiential

learning types, the talks feature didactic learning methods, providing knowledge of

contemporary research in the respective areas. One example, which took place in the

timeframe of this research, is a scientific empirical study with the CERN population,

investigating expectations on early career support from CERN12. An aim was to find

differences in the expectation of men and women. The presentation to the CERN

12 http://diversity.web.cern.ch/2016/03/support-early-careers-science-cern-understanding-expecta-tions, access 08/06/2016.

20

population, which was at the same time the object of the research was intentional, to

raise awareness on the issue.

The previous explanations show, that there are training initiatives in place at CERN

already to address the diversity of its workforce. It is aimed at different groups of

employees with varying goals, ranging from raising awareness to developing skills.

The following part of the study aims to analyse the CERN population with regard to

their perception of diversity and to give recommendations in addition to the diversity

trainings and support structures already in place.

21

4 Methodology

The following chapters will introduce the survey, used to carry out the quantitative

research, as well as the measured constructs (or subscales), the adaptations that

have been made to tailor it to the specific context of CERN and the procedure of the

data collection.

4.1 ODNA – The instrument

The Organisational Diversity Needs Analysis (ODNA) is a survey created by the so-

cial psychologist Dr. Molly Dahm (Lamarr University, USA) in 2009 (Dahm 2009). It

was designed to measure the perception and awareness of diversity in the workplace,

using eight dimensions (subscales): organisational inclusion, cultural group inclusion,

valuing differences, work load, Affirmative-Action Group Perception, trust, adaptation

and sensitivity/ flexibility.

The questions are to be rated on a five-point Likert-scale, ranging from “Strongly Dis-

agree” to “Strongly Agree”. A list of the original 53 questions, covering the dimensions

of the tool, can be found in Annex 3. Dahm constructed the questions based on the

study of literature and the learnings from previously constructed instruments, which

were used in the field, primarily the WDQ (Workforce Diversity Questionnaire), devel-

oped by Larkey (1996). Larkey’s approach was to predict communicative behaviour

to occur in diverse work teams (ibid.). Dahm altered and extended the scales accord-

ing to her own statistical and literature research to reflect the perception of diversity

among employees. Dahm conducted two field tests to ensure the validity of the new

instrument, the ODNA.

The advantage of using an existing instrument to analyse the diversity needs of an

organisation, is the reduction of risks and mistakes that can be made when using an

untested questionnaire. The ODNA can rely on previous research, statistical valida-

tion and experiences with previous diversity assessment tools. That is why it was

chosen to serve for the purpose of this study, with only slight wording adjustments to

fit the context of CERN. Furthermore, it has been used before to assess diversity

climate in companies and organisations (e.g. Brown 2008).

22

Dahm created a “general, theoretically anchored measure of diversity needs [...] used

to evaluate the existing diversity climate in an organisation” (Dahm 2009: 283). It was

constructed to identify what is important, relevant and meaningful among diverse em-

ployees. Some of the questions refer specifically to age, gender and cultural diversity

as a basis of individual perception, while others speak more broadly about group

similarities or differences. ODNA results are intended to identify attitudes based on

group identification as explained in chapter 2.1 and to what extent employees support

the organisation’s pronounced value of diversity. Dahm uses the principles and pro-

cesses of a training needs analysis, while putting an emphasis on diversity. The

scales were identified as relevant and expected to exist among a diverse workforce

(Dahm 2009).

The following section will give a description of the eight scales that are covered by

the ODNA, what they measure and how they fit into the overarching construct of di-

versity climate. In the analysis of the results, the subscales are analysed as the de-

pendent variables or “outcome variable”. Dahm divided them into two groups: the first

two dimensions are organisational dimensions, and indicate the perception of the or-

ganisation’s inclusiveness. The other six dimensions measure the individual’s views

and prejudices towards people who are different. The dimension of Valuing Differ-

ences is an exception and measures both individual attitude, as well as the perception

of their immediate work environment.

1. Cultural Group Inclusion reflects the in-group/out-group perception on a group

level. It represents two aspects: the individual’s personal identification with a cultural

group and the marginalization experiences based on that group membership. The

term “cultural group” in this case doesn’t refer to national or ethnic implications, but

rather generally to social identity groups based on a distinct demographic character-

istic.

This dimension as well as Organisational Inclusion is based on the social identity

theory, explained in chapter 2.1, which argues that individuals create their social iden-

tity by assigning themselves and the people around them to groups, based on demo-

graphic characteristics. Larkey (1996) and Schneider and Northcraft (1999) both pro-

pose, that the more individuals interact within their group and with people they share

23

a common social identity with and limit interaction with out-groups, the more groups

become differentiated from each other, which further affects patterns of interaction.

Therefore, the formation of groups has a reflexive nature (Larkey 1996: 300). The

segregation of employee groups can lead to the exclusion of minority groups in the

network of information, contacts and career advancement. The higher the score in

this subscale, the more negatively it reflects on the overall diversity climate in an

organisation. A training initiative could address groups that feel marginalized. This

subscale uses seven items/questions.

2. Organisational Inclusion reflects the in-group/out-group perception on an individual

level. It indicates the degree of affiliation the individual feels towards the organisation

(Dahm 2009: 294) and inclusion in the network of information and career opportuni-

ties. Results can show if the individual feels marginalized in the organisation based

on individual traits. For example, a person that feels excluded from the organisation,

would agree with question 8: “It seems that the real reason people are denied pro-

motions or raises is that they are not seen as fitting in.” (see Annex 3). Therefore, a

high agreement rating in this scale reflects negative on the overall diversity climate of

the organisation.

A prediction can be made when testing this dimension for the gender categories.

MorBarak et al. (1998) found in their study that “Men perceive the organisational di-

mension more favourably (more fair and inclusive) than did women […]” (ibid.: 97).

They conducted a study on the perception of diversity in an environment where men

pose the majority, similar to the CERN context. This subscale uses seven items.

3. Valuing differences. This personal dimension reflects two aspects: Firstly, the atti-

tude of the individual towards people who are different from themselves and whether

or not they perceive differences to bring added value to the organisation. The ques-

tions are constructed in a “we-mode”, underlining the positive aspects of diversity and

are meant to reflect societal platitudes about diversity (Dahm 2009: 295). The ques-

tions are proposed to indicate how much the individual is willing to support the pro-

claimed value of diversity, but not go as far as to reflect whether it is only lip-service

24

that is paid to the organisation’s value, or the individual truly supports diversity initia-

tives. The second aspect tested, is the perception of how differences are valued in

the immediate work environment.

MorBarak et al. (1998) found that “Group membership, is a powerful variable influ-

encing attitudes toward the value of diversity for the organisation” (MorBarak et al.

1998: 87). They argue that individuals of minority cultural and gender groups tend to

value differences more, than the majority group. This could be due to the fact that

minority groups are often perceived to be the one being different from the majority.

This subscale uses seven items.

4. Work load. Employees’ attitudes towards their work load has implications on their

desire to accommodate differences (Dahm 2009: 296). It is proposed that the heavier

the perceived work load is, the less open an individual is to pay attention to and em-

brace different working styles. In the evolvement of the questionnaire this scale

proved to be an important indicator of how an employee conforms to organisationally

prescribed behaviors. A higher work load therefore influences the diversity climate

negatively. This subscale uses four items.

5. Trust describes the feeling of loyalty the individual has towards its work colleagues

as well as the organisation. It brings up the notion of group identity again, which is a

possible obstacle when e.g. cultural group identity overrides commitment to the or-

ganisation (Dahm 2009: 296). Question 26 is an example for that: “People of the

same nationality, gender, belief or sexual orientation tend to look out for each other”

Results can reflect on undercurrents, despite professed valuing of differences (di-

mension 3). Trust therefore tends to be more difficult to achieve among members of

a diverse workforce (Dahm 2009). This subscale uses six items.

6. Affirmative-Action Group Perception. This dimension provides insight into the atti-

tudes employees have towards affirmative-action initiatives. Affirmative-action is a

product of the American civil rights movement in the 1960s. In essence it was per-

ceived by many companies as a governmental mandate to hire more people belong-

ing to a minority in the US. Shortly after, it has triggered many heated discussions

25

worldwide, as the preferential treatment of one group, implies necessarily a disad-

vantage for another, the majority group.

For the purpose of this study, affirmative-action is understood as the preferential treat-

ment of minority groups mainly in hiring and career advancement, but also other rel-

evant activities of an organisation. It enforces a we-they perception and can be per-

ceived as either positive or negative by individuals: “Minorities endorsed affirmative-

action programmes more than employees representing the majority.” (MorBarak et

al. 1998: 87). A high agreement score may reflect negatively on the organisation’s

diversity climate, because it can indicate a we-they perception (Dahm 2009: 296).

This dimension however has to be treated carefully. A low score can also indicate a

high percentage of majority group members, who regard affirmative-action as disad-

vantageous for themselves. This subscale uses six items.

7. Adaptation. This dimension reflects two aspects. It indicates how much the individ-

ual feels the need to adjust to colleagues’ different work styles to work effectively.

Secondly, it also reveals the motivation to do so (Dahm 2009: 296). A high agreement

rate in this scale therefore suggests a positive diversity climate. This subscale uses

seven items.

8. Sensitivity/Flexibility. This dimension picks up on Cox’s (1994) argument, that mi-

norities are and are perceived to be more sensitive to differences and flexible when

it comes to adapting to them (Dahm 2009: 297). This argument is based on the as-

sumption that minorities had to adjust to differences in the past and therefore more

flexible. The scale indicates to what degree minorities are perceived to be different

by their colleagues. A high agreement rate in this scale therefore indicates a strong

in-group/out-group perception of the employees, which can be a hindrance to the

overall diversity climate. This subscale uses seven items.

26

4.2 Adaptations to the CERN context

Without endangering the integrity of the questionnaire, some modifications have been

made in the wording of the questions to adapt them to the CERN context. The original

questionnaire has been developed in the US and therefore emphasizes aspects of

diversity that are specific to that context. One example is the use of the term “people

of color” to describe racial minorities in the US. This chapter will give an overview

over the alterations that have been made for the specific context of this study.

Some items in the original questionnaire referenced specifically to age, gender and

racioethnicity, while other items speak about broad group similarities and differences.

Dahm took over this strategy from Larkey 1996 who used specific questions as well

as general difference items, to address the difficulty in obtaining unbiased responses

when referring specifically to race and gender. Respondents directly connect the con-

cepts of racism and discrimination to these wordings, and therefore answer socially

expected, rather than stating their own opinion (Larkey 1996). The researcher took

over the interchanging use of specific and general terms, but adjusted the wording to

the context of the CERN population and the terms used in its diversity policy. There-

fore, the word “minorities” was used when specifying the groups referred to. In the

explanation of the questions for the survey respondents, the term “minority” was de-

scribed to include the diversity dimensions gender, nationality, belief, sexual orienta-

tion and physical ability.

Responses to the items were rated on a 5-point Likert-type scale and coded from 1

to 5, ranging from “strongly disagree“ (1) to “strongly agree“ (5). The only exception

is the second dimension “Organisational Inclusion”. In this dimension, a fifth option

“N/A” was added after sending out three test-surveys. It takes into account that the

performance of members of personnel under certain status at CERN are not evalu-

ated at the organisation, but by the supervisors at their home institute. This is the

case e.g. for visiting scientists and users. The additional option aims to avoid falsifi-

cation of the results.

A number of demographic questions regarding age group, gender, nationality, status

at the organisation, department, home institute (only applicable for the status of

27

“user”) and supervisory/managerial responsibilities were asked of the participants

(see Annex 5). Additionally, it was asked if the respondents “feel part of a minority at

CERN other than related to [their] gender or nationality (e.g. sexual orientation, phys-

ical ability, belief, etc.)?”. This last question however was not used in the analysis of

the survey.

4.3 Procedure

The questionnaire was designed as a randomized trial. The assessment took place

between 15 February 2016 and 10 March 2016. A purposive snowball sampling strat-

egy was adopted. “Purposive sampling is described as a random selection of sam-

pling units within the segment of the population with the most information on the char-

acteristic of interest.” (Guarte, Barrios 2006). Before the assessment, three test-sur-

veys were sent out to volunteers, after which one of the subscales was adapted (see

chapter 4.2).

The questionnaire was sent via email and posted in the Facebook group “Young at

CERN” with over 5000 members at the time of the post. The group is a platform of

exchange between current and former employees and associates of the organisation,

regardless of their status. This strategy ensured to include a variety of CERN status

in the questionnaire. Respondents were asked to confirm, that they were present at

the organisation for at least 4 months during the last year. It could therefore be as-

sumed that the participants have an adequate knowledge of their respective teams

and the organisation for the purpose of this research. They were informed, that the

questionnaire would take about 15 minutes and their answers would remain anony-

mous (Annex 4). The data analysis was conducted with SPSS.

4.4 The sample

The sample comprises 183 cases. Table 1 shows an overview over the five inde-

pendent variables13 used to group and analyse the sample.

13 Independent variables are cause variables, as opposed to the eight subscales of the ODNA, which are the outcome variables. The present study will assess how the variation in the outcome variable depends on the independent variable.

28

Table 1: Sample and independent variables

Independent variable

Groups

N %

Gender (N = 183) Male 98 54%Female

85

46%

Nationality (N = 183) European 154 84%Non-European

29

16%

Level of managerial responsibilities (N = 183)

People with supervisory responsi-bilities

41 22%

People with no supervisory respon-sibilities

142

78%

Generation (Age) (N = 182) Generation X (36-45) 34 19%

Generation Y (26-35) 104 57%Generation Z (18-25)

44

24%

CERN Status (N = 170) Staff 39 23%

Fellow 33 19%

Doctoral Student 29 17%

Student (Admin Student, Technical Student, Trainee)

29 17%

User 40 24%

The study sample comprised of 53% men and 47% women. This does not reflect the

overall population of CERN, in which women make out 20% (see Figure 1).

Figure 1: Gender distribution of sample and CERN population14

14 CERN Annual Personnel Statistics 2015: http://cds.cern.ch/record/2154389/files/CERN-HR-STAFF-STAT-2015.pdf?version=1

54%

46%

Survey respondents

Male Female

81%

19%

CERN population (2015)

Male Female

29

The variable of managerial or supervisory responsibilities was dichotomized in true

or false, without differentiating the level of supervisory responsibility to maintain the

anonymity of the respondents. 22% of the respondents indicated to have a supervi-

sory role at CERN. As a result, the group of people with managerial responsibilities

is heterogeneous and ranges from employees supervising students to department

heads. There is no public data available to compare the composition of the survey

respondents with the CERN population for this variable.

The nationality variable was also dichotomized, into Europeans and Non-Europeans

to ensure a sufficient group size to compare. CERN was founded as a European

laboratory and the majority of the member states are still European. It is therefore

assumed that Europeans are in the majority, while Non-Europeans are the minority

at the organisation, since no public data is available to compare the composition of

the survey respondents with the CERN population. This is also reflected in the sample

(Non-Europeans make out 16%). However, the group of Non-European consists of

52% (15 cases) US nationals. This majority can influence the results significantly and

has to be taken into account when interpreting the data.

Age groups were identified by generational categories, to test if there are differences

in perception between the widely used differentiation of generations: Generation Z,

which is at the time of the study aged between 18 and 25 years (19%), Generation Y,

which is aged between 26 and 35 years (57%) and Generation X which is between

36 and 55 years (19%). Compared to the overall age distribution of the CERN popu-

lation, it can be noted, that the average age of the survey respondents is much

younger, that the CERN average. Figure 2 shows a clear shift of the Bell curve of the

two groups.

30

Figure2: Composition of survey respondents and CERN population: Generation (Age)

The fifth independent variable is CERN status. CERN has various status, but for the

purpose of this study, the most common once were selected to ensure a sufficient

group size. This leads to the exclusion of 13 cases, for the analysis of this independ-

ent variable, because the cases could not be assigned to the selected groups.

CERN staff are employees, which is also valid for the group of fellows. The latter

however are graduates and entry-level employees with a short-term contract up to

three years. The group of Doctoral students are associated with and paid by CERN,

taking over organisational responsibilities, but at the same time completing their doc-

toral thesis with a university. The group of students merges various types of interns

at CERN at university level, who are therefore also associated with a university,

spending up to 14 months at the organisation.

The group of users is comprised of mostly visiting scientists, associated with research

institutes (and employed by them), carrying out their research at CERN. For this

group, CERN is merely a place to work, not an employer. Often the supervisor is not

present at CERN, but at their home institute. Users are the biggest group of the CERN

population with a share of 70%. However, many of them spend only part of their work-

ing time at CERN (this ranges from a couple of days a year to a permanent stay). To

avoid biasing the data, respondents were asked to confirm, that they have spent at

least 4 months in the last year on CERN premises. Users are also the biggest group

0%

10%

20%

30%

40%

50%

60%

Generation Z (18-25) Generation Y (26-35) Generation X (36-55) Above

Survey respondents CERN population (2015)

31

of survey respondents. The respondent rate of students, doctoral students and fel-

lows are exceptionally high, which can be ascribed to the sampling method, using the

social media platform Facebook, which is very often used by students and young

adults.

Figure3: Composition of survey respondents and CERN population15: CERN Status

For each of the independent variables a hypothesis was formulated, which will be

tested with statistical data analysis:

H1 There is a difference in the diversity perspectives based on gender.

H2 There is a difference in the diversity perspectives based on nationality.

H3 There is a difference in the diversity perspectives based on level of manage-

rial responsibilities.

H4 There is a difference in the diversity perspectives based on generations.

H5 There is a difference in the diversity perspectives based on status at the

organisation.

15 CERN Annual Personnel Statistics 2015: http://cds.cern.ch/record/2154389/files/CERN-HR-STAFF-STAT-2015.pdf?version=1

0% 10% 20% 30% 40% 50% 60% 70% 80%

Other(not included in analysis)

User

Student

Doctoral Student

Fellow

Staff

CERN population (2015) Survey respondents

32

4.5 Method of analysis

The following chapter will explain the statistical tests used to analyse the results of

the survey.

Descriptive statistics (mean, standard deviation) were calculated for every subscale.

To test the reliability of the subscales, Cronbach’s α was calculated for all subscales.

The Pearson correlation was used to measure the degree of relation between the

dimensions. The strength of the relationship between the dimensions is analysed us-

ing the following guidelines: small r = .10 to .29, medium r =.30 to .49, and large r=.50

to 1.0 (Cohen 1988).

The Independent t-test was applied to compare the means of gender, nationality and

managerial responsibilities (see table 1). The t-test assesses whether the mean of

two groups are statistical significantly different from each other. The t-test assumes

that the sample is derived from a normally distributed population and that the data is

measured at least at the interval level. 20 participants per group are required to get a

large effect size (Cohen 1992). The test was conducted with all eight dimensions:

organisational inclusion, cultural group inclusion, valuing differences, work load, trust,

Affirmative-Action Group Perception, adaptation and sensitivity/flexibility.

The one-way ANOVA (Analysis of variance) is a statistical procedure, that tests the

overall fit of a linear model and the statistically significant difference of means when

more than two groups are being compared. It compares the amount of systematic

variance in the data to the amount of unsystematic variance. When a statistically sig-

nificant difference is detected, a Tukey post-hoc analysis is conducted to identify the

groups that differ from each other. It compares simultaneously the means of one

group to the means of any other group, basically conducting a simultaneous inde-

pendent t-test with all groups.

The following three assumptions should be tested prior to running ANOVAs: The data

should be normally distributed, homogeneity of variance needs to be ensured and the

data is measured on at least an interval scale. ANOVA has been conducted to test

the eight dimensions of the diversity climate with two independent variables: age

groups and CERN status (see table 1).

33

For the independent t-test, as well as the ANOVA, normal distribution was tested

using the Kolmogorov-Smirnoff test. The data was tested for homogeneity of variance

using Levene’s statistic. If homogeneity of the variances is not given, the Welch cor-

rection has to be applied, which is an adaptation of the t-test assuming unequal vari-

ances.

5 Data analysis

In the following section, the process and the results of the statistical data analysis are

described. Initially, the sample will be analysed as a whole, reflecting the diversity

climate in the organisation, with the help of descriptive statistics and the correlations

of the dimensions. After that, it will be tested whether the preconditions for the de-

scribed procedures are fulfilled. Then, the results of the analysis for each of the five

hypotheses are described. Each independent variable will be tested with each diver-

sity climate dimension. There will be a summary of the results at the end of this chap-

ter (see page 62).

5.1 Descriptive statistics and correlations of the subscales

Table 2 shows the means for all tested dimensions of the diversity climate, as well as

the Pearson r, indicating the correlations between the dimensions. A high mean gen-

erally suggests a negative implication for the diversity climate, while M = 3 shows a

neutral position. There are three subscales which are reverse: Valuing Differences,

Trust and Adaptation. In these scales, a high score has positive implications for the

diversity climate.

34

Table 2: Descriptive Statistics and correlations of the eight dimensions and overall diver-sity climate

Variable M SD 1 2 3 4 5 6 7

1. Cultural Group Inclusion 2.62 .97

2. Organisational Inclusion 2.54 .99 .74**

3. Valuing Differences 3.35 .69 -.73** - .62**

4. Work Load 2.94 1.09 .27** .32** -.32**

5. Trust 3.37 .64 -.56** -.61** .61** -.24**

6. Affirmative-Action Group Perception 3.11 .74 .29** .30** -.23** .21** -.14

7. Adaptation 3.94 .49 .25** .18* -.11 .15* -.06 .43**

8. Sensitivity/Flexibility 2.98 .67 .31** .36** -.16* .15* .04 .41** .41**

Note: M = mean; SD = standard deviation; The correlations are based on 183 subordinates (N = 183).

* p < .05. **p < .01.

Generally, it can be concluded, that the respondents stayed mostly neutral in their

answers, but there are tendencies, which can be identified.

Regarding the feeling of inclusiveness of the CERN population (subscale 1 + 2), peo-

ple have a neutral perception, but leaning towards disagreeing to being marginalized

as an individual (M (Organisational Inclusion) = 2.54), as well as a part of a cultural

group M (Cultural Group Inclusion) = 2.54). For these two dimensions it will be signif-

icant to compare majority and minority group perceptions (chapter 5.3).

A tendency to support the CERN value of diversity can be determined (M (Valuing

Differences) = 3.35), as well as the observance that colleagues do the same.

The perception of the work load was rated neutral without a significant tendency,

however the standard deviation is significantly high, which indicates significant differ-

ences between groups. The results in chapter 5.3 suggest that supervisors, as well

as users and doctoral students regard their work load as overwhelming, while stu-

dents and fellows disagree with the notion of being overloaded.

When it comes to trust toward the organisation as an employer (or hosting institute),

answers stayed also neutral (M (Trust) = 3.37). However, this result also means that

e.g. the statement “I feel confident that CERN will always try to treat me fairly” was

evaluated neutrally rather than confirmative, which can suggest a lack of trust thereof.

The only dimension which shows a statistically significant tendency towards one side

is the dimension of adaptation (M (Adaptation) = 3.94). The data shows that the

35

CERN population is open to adapting to the differences of their colleagues and rec-

ognize the benefit of a diverse workforce. This is a positive indicator for the overall

diversity climate.

The dimension of sensitivity and flexibility indicates whether minority groups are being

perceived (and treated) as different. The results show a generally neutral perception

by the CERN population. For this dimension, it will be interesting to identify whether

majority groups have a significantly different attitude compared to minority groups.

Table 2 demonstrates the relationship between the eight dimensions of the diversity

climate. The results show that there were positive and negative correlations between

each of the eight dimensions.

There is a strong positive correlation between Cultural Group Inclusion and Organi-

sational Inclusion (r =.74). Therefore, Cultural Group Inclusion is perceived to be

strongly associated with Organisational Inclusion. That means that the individual feel-

ing of inclusion in the organisation is directly related to the belonging to a cultural

group and how that cultural group is perceived to be included.

There was a large negative correlation between Cultural Group Inclusion (as well as

Organisational Inclusion) and Valuing Differences (r = -.73). This is due to the fact,

that the Valuing differences subscale is reversed. It means that the more an individual

identifies with a cultural group and feels this cultural group is included in the organi-

sation (as well as an individual), the more the individual is likely to support the as-

sumption that differences bring a positive contribution to the work environment at

CERN.

As predicted, another strong correlation exists between Trust and Valuing Differ-

ences: The more the individual trusts the organisation rather than their own cultural

group, the more it values differences and supports a diverse workforce.

5.2 Test of preconditions for statistical analysis

Interval measurement. To measure on an interval level means that the collected data

is measured in an ordered scale with assumed same distances between each inter-

val. Thus, “distances” are equivalent along the scale from the low interval to the high

interval. In this case, the 5-point Likert scale, used to measure the 8 dimensions from

36

“strongly disagree” to “strongly agree” is indeed an ordered scale (ranked from 1 to

5) and the distances between the measurements are assumed to be equal for the

purpose of this study.

Reliability. The Cronbach’s α were calculated for all subscales to test reliability of the

53 items, meaning whether the items of a subscale correlate with each other posi-

tively and therefore measure the same construct. A Cronbach’s α of .6 and above

was assumed to prove reliability (see Annex 6 for the Cronbach’s α of all dimensions).

All items except of three proved reliability. Items 27 (Trust), 33 and 35 (both Affirma-

tive-Action Group Perception) were removed before the analysis, due to insufficient

reliability.

Normal distribution. The Kolmogorov-Smirnov Test was used to examine whether the

sample comes from a group, which is normally distributed, by comparing the defined

group to a normally distributed reference group. All dependent and independent var-

iables have been tested for normality. For all groups, the significance level was below

.05, which indicates not normally distributed groups. However, Eid et al. (2013) indi-

cate that the t-test and ANOVA are still reliable if the sample size is > 30. Therefore,

even though the precondition of normal distribution was not fully met, the t-test and

ANOVA are used for the analysis.

Test of homogeneity of variance. For each independent variable and dimension,

Levene’s test was applied to test for equal variances across the tested groups. Find

the results of the calculations in Annex 7. All except two cases proved equal vari-

ances. In the cases of unequal variances, the Welch correction is applied (Eid et al.

2013). Annex 7 shows the results of the t-test and ANOVA test for both cases: equal

and unequal variances.

5.3 Test of hypotheses

The following chapter gives a description of the results of the statistical tests con-

ducted. The mathematical explanations of the calculations are not explained. The

numbers can be found in Annex 7, together with the test for equal variances. Statis-

tical significance was determined based upon a significance level of p < 0.05.

37

When differences occur between the groups, it suggests that interactions in social

encounters in the organisation are determined to varying degrees by the participants’

membership to a group (gender, nationality, age) (MorBarak et al. 1998: 99).

5.3.1 Results for eight dimensions: H1 Gender

H1 There is a difference in the diversity perspectives based on gender.

The following results indicate that hypothesis 1 was confirmed. The perception dif-

fered significantly in the dimensions Cultural Group Inclusion, Organisational Inclu-

sion, Valuing Differences, Affirmative-Action Group Perception, Adaptation and

Sensitivity/Flexibility.

Gender – Cultural Group Inclusion.

There was a significant difference (t(181) = 3.32, p < 0.05) in the perception of women

(M = 2.87, SD = .97) and men (M = 2.40, SD = .92). Women and men at CERN do

not share similar perceptions regarding Cultural Group Inclusion. While women have

a neutral perception towards whether minority groups are integrated at CERN, men

reject the notion of demographic groups being marginalized.

Table 3: Means and standard deviation for women and men: Cultural Group Inclusion Gender

N

M

SD

Women

85

2.87

.97

Men

98 2.40 .92

Note: N = 183. M = mean; SD = standard deviation

When looking at question 2, an item suggested by Dahm (2009: 295) to be a strong

indicator of the dimension of Cultural Group Inclusion, it shows that 43% of men

strongly disagree with the notion, that their work is judged based on whether their

behaviour conforms to the organisational norm. At the same time only 27% of women

strongly disagree with that statement and 28% agree or strongly agree. Therefore,

the minority group of women have a more negative perception of the marginalization

of cultural groups, than the majority group.

38

Figure 4: Detailed results for question 2 (Cultural Group Inclusion): Gender

The overall perception of Cultural Group Inclusion can be evaluated as neutral,

which indicates that exclusion practices are not absent, but also not seen as preva-

lent.

Gender – Organisational Inclusion

The results indicate that there is a significant difference (t(181) = 3.23, p < 0.05) in

the perception of women (M = 2.79, SD = 1.02) and men (M = 2.32, SD = .90). Women

and men do not share a similar perception regarding Organisational Inclusion and

exclusion practices. Men generally reject the notion of marginalisation of individuals

who are different, whereas women, as the minority group at CERN have a more neu-

tral point of view.

Table 4: Means and standard deviation for women and men: Organisational Inclusion Gender

N

M

SD

Women

85

2.79

1.02

Men

98 2.32 .90

Note: N = 183. M = mean; SD = standard deviation

When looking at item 8, which is noted by Dahm (2009: 294) as particularly significant

for this subscale, it confirms the calculation and reveals, that 25% of the men strongly

disagree with the statement, that people are overlooked in promotions because of not

conforming to the majority, whereas only 13% of women strongly disagree with the

statement. However, in both groups, approximately 48% either strongly disagree or

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

Female

Question 2: "Sometimes people who talk and act differently are treated like they aren’t capable or smart." (N=183)

Strongly Disagree Disagree Neutral Agree Strongly Agree

39

disagree with the statement, giving a generally positive indicator for the diversity cli-

mate.

Figure 5: Detailed results for question 8 (Organisational Inclusion): Gender

Gender – Valuing Differences

There is a small significant difference (t(181) = -3.10, p < 0.05) in the perception of

women (M = 3.19, SD = .72) and men (M = 3.50, SD = .64). Men and women are

generally neutral, whereas men perceive the valuing of differences more positively at

the organisation.

Table 5: Means and standard deviation for women and men: Valuing Differences Gender

N

M

SD

Women

85

3.19

.72

Men

98 3.50 .64

Note: N = 183. M = mean; SD = standard deviation

The results of question 15, which tested the perception of how the immediate work

environment values differences, shows that while 48% of men agree with the state-

ment, only 35% of women do (Figure 6).

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

Female

Question 8: "It seems that the real reason people are denied promotions or raises ist that they are seen as not fitting in" (N=166)

Strongly Disagree Disagree Neutral Agree Strongly Agree

40

Figure 6: Detailed results for question 15 (Valuing Differences): Gender

Gender – Work Load

The data indicates no significant difference (t(181) = .52, p > 0.05) in the perception

of women (M = 2.98, SD = 1.09) and men (M = 2.90, SD = 1.09). Therefore, women

and men at CERN share similar perceptions regarding work load, which is a neutral

one.

Table 6: Means and standard deviation for women and men: Work load Gender

N

M

SD

Women

85

2.98

1.09

Men

98 2.90 1.09

Note: N = 183. M = mean; SD = standard deviation

Gender – Trust

There is no significant difference t(181) = -.60, p > 0.05) in the perception of women

(M = 3.34, SD = .60) and men (M = 3.39, SD = .67) regarding trust towards the or-

ganisation. Men and women share a neutral perception.

Table 7: Means and standard deviation for women and men: Trust Gender

N

M

SD

Women

85

3.39

.60

Men

98 2.90 .67

Note: N = 183. M = mean; SD = standard deviation

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

Female

Question 15: When people have a different orientation or style, they take the time to explain and try to understand the other person's point of view. (N=183)

Strongly Disagree Disagree Neutral Agree Strongly Agree

41

Gender – Affirmative-Action Group Perception

The results demonstrate a small significant difference t(181) = 2.50, p > 0.05) in the

perception of men (M = 2.98, SD = .73) and women (M = 3.26, SD = .72) towards

affirmative-action initiatives. While for both groups the perception is generally neutral,

women have a slightly more positive attitude, which corresponds to the expectations

according to MorBarak et al. (1998) who prognose a more positive attitude of minority

groups, which are the beneficiaries of such initiatives.

Table 8: Means and standard deviation for women and men: Affirmative-Action Group Per-ception Gender

N

M

SD

Women

85

3.26

.72

Men

98 2.98 .73

Note: N = 183. M = mean; SD = standard deviation

Gender – Adaptation

The results of the t-test show that there is a small significant difference t(174.198) =

3.14, p < 0.05) in the perception of women (M = 4.05, SD = .38) and men (M = 3.83,

SD = .54). Both groups have a clear positive attitude towards adapting to their diverse

work environment, whereas women at CERN are slightly more open than men.

Table 9: Means and standard deviation for women and men: Adaptation Gender

N

M

SD

Women

85

4.05

.38

Men

98 3.83 .54

Note: N = 183. M = mean; SD = standard deviation

One of the questions, regarded as a significant indicator for this dimension by Dahm

(2009: 296) is item 40:

42

Figure 7: Detailed results for question 40 (Adaptation): Gender

It shows that overall only 8% disagree with the notion to learn about other peoples’

cultural backgrounds, while for both groups around 20% strongly agree.

Gender – Sensitivity/Flexibility The results of the t-test demonstrate a small significant difference t(181) = 2.97, p <

0.05) in the perception of men (M = 2.84, SD = .67) and women (M = 3.14, SD = .64)

regarding sensitivity and flexibility. Both groups have a rather neutral attitude towards

minorities being more sensible to differences and ready to adapt to them. However,

women have a slightly stronger agreement with statements like “It seems that minor-

ities have a special sensitivity and understanding of diversity issues.” This overall

neutral perception points to a positive diversity climate. Since a strong positive per-

ception suggests a strong in-group/out-group perception, meaning minorities are per-

ceived as different and treated as an out-group.

Table 10: Means and standard deviation for Europeans and Non-Europeans: Sensitiv-ity/Flexibility

Gender

N

M

SD

Women

85

3.14

.64

Men

98 2.84 .67

Note: N = 183. M = mean; SD = standard deviation

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

Female

Question 40: "I go out of my way to learn about others‘ cultural backgrounds, traditions and points of view." (N=183)

Strongly Disagree Disagree Neutral Agree Strongly Agree

43

5.3.2 Results for eight dimensions: H2 Nationality

H2 There is a difference in the diversity perspectives based on nationality.

The following results indicate that hypothesis 2 was confirmed. The perceptions

based on nationality differed in the dimensions Affirmative-Action Group Perception

and Sensitivity/Flexibility.

Nationality – Cultural Group Inclusion

The data shows that there is no significant difference (t(181) = 1.81, p > 0.05) in the

perception of Europeans (M = 2.56, SD = .95) and Non-Europeans (M = 2.92, SD =

1.04). Europeans and Non-Europeans at CERN share a similar neutral perception

regarding Cultural Group Inclusion.

Table 11: Means and standard deviation for Europeans and Non-Europeans: Cultural Group Inclusion

Nationality

N

M

SD

European

154

2.56

.95

Non-European

29 2.92 1.04

Note: N = 183. M = mean; SD = standard deviation

Nationality – Organisational Inclusion 

Regarding Organisational Inclusion there is no significant difference t(181) = .144, p

> 0.05) in the perception of Europeans and Non-Europeans. Therefore Europeans (M

= 2.53, SD = .96) and Non-Europeans (M = 2.56, SD = 1.10 ) at CERN share the

same neutral perception towards Organisational Inclusion.

Table 12: Means and standard deviation for Europeans and Non-Europeans: Organisa-tional Inclusion

Nationality

N

M

SD

European

154

2.53

.96

Non-European

29 2.56 1.10

Note: N = 183. M = mean; SD = standard deviation

44

Nationality – Valuing Differences

There is no significant difference ((t(181) = -1.623, p > 0.05) in the perception of Eu-

ropeans (M = 3.39 , SD = .66) and Non-Europeans (M = 3.16, SD = .82). Europeans

as well as Non-Europeans at CERN have an equally neutral perception of valuing of

differences.

Table 13: Means and standard deviation for Europeans and Non-Europeans: Valuing Differ-ences

Nationality

N

M

SD

European

154

3.39

.66

Non-European

29 3.16 .82

Note: N = 183. M = mean; SD = standard deviation

Nationality – Work Load

The independent t-test shows no significant difference (t(181) = 1.77, p > 0.05) in the

perception for Europeans (M = 2.87, SD = 1.10) and Non-Europeans (M = 3.26, SD

= .99). Thus, Europeans and Non-European at CERN share similar perceptions re-

garding Work Load.

Table 14: Means and standard deviation for Europeans and Non-Europeans: Work Load

Nationality

N

M

SD

European

154

2.87

1.10

Non-European

29 3.26 .99

Note: N = 183. M = mean; SD = standard deviation

Nationality – Trust

There is no significant difference t(181) = 407, p > 0.05) in the perception of Non-

Europeans (M = 3.41, SD = .76) and Europeans (M = 3.36, SD = .61). Therefore,

Europeans and Non-Europeans at CERN share similar perception regarding trust to-

wards the organisation.

45

Table 15: Means and standard deviation for Europeans and Non-Europeans: Trust Nationality

N

M

SD

European

154

3.41

.76

Non-European

29 3.36 .61

Note: N = 183. M = mean; SD = standard deviation

Nationality – Affirmative-Action Group Perception

The results demonstrate a small, but significant difference (t(181) = 2.98, p < 0.05)

in the perception of Europeans (M = 3.04, SD = .74) and Non-Europeans (M = 3.48,

SD = .59) regarding affirmative-action initiatives. Non-Europeans have a more posi-

tive attitude. Since the majority of the Non-European group indicated to be from the

USA, the origin of the affirmative-action movement, the result can be lead back to a

historically negative attitude towards favouring one demographic group over another

(see chapter 4.1).

Table 16: Means and standard deviation for Europeans and Non-Europeans: Affirmative-Action Group Perception

Nationality

N

M

SD

European

154

3.04

.74

Non-European

29 3.48 .59

Note: N = 183. M = mean; SD = standard deviation

Nationality – Adaptation

The results indicate no significant difference t(181) = 1.307, p > 0.05) in the percep-

tion of Europeans and Non-Europeans. Thus, Europeans (M = 4.04 , SD = .41) and

Non-Europeans (M = 3.91 , SD = .50 ) at CERN share a similar open perception

towards adapting to colleagues who might be different.

46

Table 17: Means and standard deviation for Europeans and Non-Europeans: Adaptation Nationality

N

M

SD

European

154

4.04

.41

Non-European

29 3.91 .50

Note: N = 183. M = mean; SD = standard deviation

Nationality – Sensitivity / Flexibility

The results demonstrate a small, but significant difference t(181) = 2.00, p < 0.05) in

the perception of Europeans (M = 2.94, SD = .68) and Non-Europeans (M = 3.20, SD

= .59) regarding Sensitivity/Flexibility. The minority group of Non-Europeans perceive

minorities in general to be more sensitive and flexible when it comes to a diverse work

environment.

Table 18: Means and standard deviation for Europeans and Non-Europeans: Sensitiv-ity/Flexibility

Nationality

N

M

SD

European

154

2.94

.68

Non-European

29 3.20 .59

Note: N = 183. M = mean; SD = standard deviation

When looking at question 45, proposed by Dahm (2009) as a good indicator for the

dimension, it shows, that 47% of Europeans, who are the majority group at CERN

perceive minorities to be different from the rest of the organisation (Figure 8).

Figure 8: Detailed results for question 45 (Sensitivity/Flexibility): Nationality

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

European

Non-European

Question 45: "It seems that minorities have a special sensitivity and understanding of diversity issues." (N=183)

Strongly Disagree Disagree Neutral Agree Strongly Agree

47

5.3.3 Results for eight dimensions: H3 Managerial responsibilities

H3 There is a difference in the diversity perspectives based on level of managerial

responsibilities.

The following results indicate that hypothesis 3 was not confirmed. The perception

only differs in the dimension work load, but not in any other dimension. By itself the

dimension work load cannot be an indicator of an overall diversity climate (Dahm

2009).

Managerial responsibilities – Cultural Group Inclusion

The results indicate that there is no significant difference (t(181) = -.953, p > 0.05) in

the perception of employees with no supervisory responsibilities (M = 2.58, SD = .96)

and with supervisory responsibilities (M = 2.74, SD = .99). Employees with or without

supervisory responsibilities share a similar perception regarding Cultural Group In-

clusion.

Table 19: Means and standard deviation for people with and without managerial responsi-bilities: Cultural Group Inclusion

Supervisor

N

M

SD

No

142

2.58

.96

Yes

41 2.74 .99

Note: N = 183. M = mean; SD = standard deviation

Managerial responsibilities – Organisational Inclusion

The results demonstrate a small, but statistically not significant difference t(181) = -

.736, p > 0.05) in the perception of employees with no supervisory responsibilities (M

= 2.51, SD = .94) and employees with supervisory responsibilities (M = 2.64, SD =

1.12) regarding Organisational Inclusion. Therefore, employees with and without su-

pervisory responsibilities share similar perceptions regarding Organisational Inclu-

sion.

48

Table 20: Means and standard deviation for people with and without managerial responsi-bilities: Organisational Inclusion

Supervisor

N

M

SD

No

142

2.51

.94

Yes

41 2.64 1.12

Note: N = 183. M = mean; SD = standard deviation

Managerial responsibilities – Valuing Differences

The results of the independent t-test show, that there is no statistically significant

difference (t(181) = .018, p > 0.05) in the perception of employees with no supervisory

responsibilities (M = 3.35, SD = .69) and with supervisory responsibilities (M = 3.35,

SD = .72). Employees with or without supervisory responsibilities share a similar per-

ception of Valuing Differences.

Table 21: Means and standard deviation for people with and without managerial responsi-bilities: Valuing Differences

Supervisor

N

M

SD

No

142

3.35

.69

Yes

41 3.35 .72

Note: N = 183. M = mean; SD = standard deviation

Managerial responsibilities – Work Load

The independent t-test shows a significant difference (t(181) = -2.46, p < 0.05) in the

perception of employees with no supervisory responsibilities (M = 2.83, SD = 1.09)

and employees with supervisory responsibilities (M = 3.30, SD = 1.02). Both groups

regard their workload generally neutral, however employees with supervisory roles

tend to agree more with the notion to be overloaded with work.

49

Table 22: Means and standard deviation for people with and without managerial responsi-bilities: Work load

Supervisor

N

M

SD

No

142

2.83

1.09

Yes

41 3.30 1.02

Note: N = 183. M = mean; SD = standard deviation

Managerial responsibilities – Trust

There is no significant difference t(181) = -.458, p > 0.05) in the perception of em-

ployees with no supervisory function (M = 3.35, SD = .67) and employees with super-

visory function (M = 3.40, SD = .51). Therefore, employees with or without supervisory

responsibilities share a similar level of trust towards the organisation.

Table 23: Means and standard deviation for people with and without managerial responsi-bilities: Trust

Supervisor

N

M

SD

No

142

3.35

.67

Yes

41 3.40 .51

Note: N = 183. M = mean; SD = standard deviation

Managerial responsibilities – Affirmative-Action Group Perception

The results demonstrate a small but statistically not significant difference t(181) = -

.262, p > 0.05) in the perception of employees with no supervisory responsibilities (M

= 3.10, SD = .77) and employees with supervisory responsibilities (M = 3.14, SD =

.64) regarding affirmative-action initiatives.

Table 24: Means and standard deviation for people with and without managerial responsi-bilities: Affirmative-Action Group Perception

Supervisor

N

M

SD

No

142

3.10

.77

Yes

41 3.14 .64

Note: N = 183. M = mean; SD = standard deviation

50

Managerial responsibilities – Adaptation

The independent t-test indicates no significant difference (t(181) = -.082, p > 0.05) in

the perception of employees with or without supervisory responsibilities. Thus, em-

ployees with no supervisory responsibilities (M = 3.93 , SD = .52) and employees with

supervisory responsibilities (M = 3.94 , SD = .39 ) at CERN share a similar neutral

attitude concerning the need and openness to adapt to their colleagues.

Table 25: Means and standard deviation for people with and without managerial responsi-bilities: Adaptation

Supervisor

N

M

SD

No

142

3.93

.52

Yes

41 3.94 .39

Note: N = 183. M = mean; SD = standard deviation

Managerial responsibilities – Sensitivity/Flexibility

The results demonstrate a small but not statistically significant difference t(181) = -

.759, p > 0.05) regarding sensitivity and flexibility.

Table 26: Means and standard deviation for people with and without managerial responsi-bilities: Sensitivity/Flexibility

Supervisor

N

M

SD

No

142

2.96

.68

Yes

41 3.04 .66

Note: N = 183. M = mean; SD = standard deviation

5.3.4 Results for eight dimensions: H4 Generation (Age)

H4 There is a difference in the diversity perspectives based on generations.

The following results indicate, that hypothesis 4 was not confirmed. None of the eight

tested dimensions of diversity climate differ based on generations.

51

Table 27: ANOVA for eight dimensions: Generation (Age)

Dimension

Sig.

Cultural Group Inclusion .294

Organisational Group Inclusion .510

Valuing Differences .308

Work Load .318

Trust .654

Affirmative-Action Group Perception .578

Adaptation 579

Sensitivity/Flexibility .545

Note: N = 182 *p < .05. *** p <.001.

Generation (Age) – Cultural Group Inclusion

As determined by ANOVA (F(2, 179) = 1.233, p= .294), there is no statistically signif-

icant difference between the three age groups regarding Cultural Group Inclusion.

Table 28: Means and standard deviation for the generational groups: Cultural Group Inclu-sion

Generation (Age)

N

M

SD

Generation Z (18- 25)

34

2.75

.92

Generation Y (26-35)

104 2.66 1.01

Generation X (36-45)

44 2.43 .93

Note: N = 182; M = mean; SD = standard deviation

Generation (Age) – Organisational Inclusion

As determined by ANOVA (F(2, 179) = .676, p= .510), there is no statistically signifi-

cant difference between the three age groups regarding Organisational Inclusion.

52

Table 29: Means and standard deviation for the generational groups: Organisational Inclu-sion

Generation (Age)

N

M

SD

Generation Z (18- 25)

34

2.70

.17

Generation Y (26-35)

104 2.54 .10

Generation X (36-45)

44 2.44 .15

Note: N = 182; M = mean; SD = standard deviation

Generation (Age) – Valuing Differences

As determined by ANOVA (F(2, 179) = 1.186, p= .308), there is no statistically signif-

icant difference between the three age groups regarding the valuing of differences.

Table 30: Means and standard deviation for the generational groups: Valuing Differences Generation (Age)

N

M

SD

Generation Z (18- 25)

34

3.37

.68

Generation Y (26-35)

104 3.29 .72

Generation X (36-45)

44 3.48 .64

Note: N = 182; M = mean; SD = standard deviation

Generation (Age) – Work Load

As determined by ANOVA (F(2, 179) = 1.154, p= .318), there is no statistically signif-

icant difference between the three age groups regarding Work Load.

Table 31: Means and standard deviation for the generational groups: Work Load Generation (Age)

N

M

SD

Generation Z (18- 25)

34

2.96

1.18

Generation Y (26-35)

104 3.03 1.09

Generation X (36-45)

44 2.73 1.02

Note: N = 182; M = mean; SD = standard deviation

53

Generation (Age) – Trust

As determined by ANOVA (F(2, 179) = .426, p= .654), there is no statistically signifi-

cant difference between the three age groups regarding trust towards the organisa-

tion.

Table 32: Means and standard deviation for the generational groups: Trust Generation (Age)

N

M

SD

Generation Z (18- 25)

34

3.32

.60

Generation Y (26-35)

104 3.35 .66

Generation X (36-45)

44 3.44 .63

Note: N = 182; M = mean; SD = standard deviation

Generation (Age) – Affirmative-Action Group Perception

As determined by ANOVA (F(2, 179) = .551, p= .579), there is no statistically signifi-

cant difference between the three age groups regarding the perception of affirmative-

action initiatives.

Table 33: Means and standard deviation for the generational groups: Affirmative-Action Group Perception

Generation (Age)

N

M

SD

Generation Z (18- 25)

34

3.21

.65

Generation Y (26-35)

104 3.12 .79

Generation X (36-45)

44 3.03 .72

Note: N = 182; M = mean; SD = standard deviation

Generation (Age) – Adaptation

As determined by ANOVA (F(2, 179) = .745, p= .476), there is no statistically signifi-

cant difference between the three age groups regarding Adaptation.

54

Table 34: Means and standard deviation for the generational groups: Adaptation Generation (Age)

N

M

SD

Generation Z (18- 25)

34

4.00

.51

Generation Y (26-35)

104 3.94 .47

Generation X (36-45)

44 3.87 .53

Note: N = 182; M = mean; SD = standard deviation

Generation (Age) – Sensitivity/Flexibility

As determined by one-way ANOVA (F(2, 179) = .610, p= .545), there is no statistically

significant difference between the three age groups regarding sensitivity and flexibil-

ity.

Table 35: Means and standard deviation for the generational groups: Sensitivity/Flexibility Generation (Age)

N

M

SD

Generation Z (18- 25)

34

2.88

.64

Generation Y (26-35)

104 3.02 .68

Generation X (36-45)

44 2.95 .69

Note: N = 182; M = mean; SD = standard deviation

5.3.5 Results for eight dimensions: H5 CERN Status

H5 There is a difference in the diversity perspectives based on status at the organi-

sation.

The following results indicate that hypothesis 5 was confirmed. The results differed in

the dimensions of Cultural Group Inclusion, Valuing Differences and Work Load.

55

Table 36: ANOVA for eight dimensions: CERN Status Dimension

Sig.

Cultural Group Inclusion .040*

Organisational Group Inclusion .113

Valuing Differences .013*

Work Load .000***

Trust .592

Affirmative-Action Group Perception .054

Adaptation .592

Sensitivity/Flexibility .512

Note: N = 170 *p < .05. *** p <.001.

CERN Status – Cultural Group Inclusion

As determined by ANOVA (F(4, 165) = .716, p= .04), there is a statistically significant

difference between the groups based on the CERN Status regarding Cultural Group

Inclusion. A Tukey post-hoc test revealed, that students have a very positive percep-

tion of how cultural groups are included in the organisation. This perception is statis-

tically significantly different from the perception of doctoral students as well as users,

who tend to be more neutral.

Table 37: Means and standard deviation for CERN Status: Cultural Group Inclusion CERN Status

N

M

SD

Staff

39

2.64

.89

Fellow

33 2.69 1.03

Doctoral Student

29 2.84 1.02

Student

29 2.14 .90

User

40 2.79 .97

Note: N = 170; M = mean; SD = standard deviation

When having a look at the answers to question 2 (Figure 9), which was specified by

Dahm (2009: 295) as a significant indicator for the dimension, it shows that 72% of

56

the students disagree with the notion that people who are different are being margin-

alized, while it is only 52% (Doctoral students) and 60% (Users) for the other two

groups. This still indicates an overall rejection of the marginalization of cultural

groups. This is specifically shown by the high rate of “strongly disagree” answers by

all groups.

Figure 9: Detailed results of question 2 (Cultural Group Inclusion): CERN Status

CERN Status – Organisational Inclusion

As determined by ANOVA (F(4, 165) = 1.89, p= .113), there is no statistically signifi-

cant difference between the CERN status regarding Organisational Inclusion.

Table 38: Means and standard deviation for CERN Status: Organisational Inclusion CERN Status

N

M

SD

Staff

39

2.55

.94

Fellow

33 2.54 .95

Doctoral Student

29 2.71 1.00

Student

29 2.11 .86

User

40 2.71 1.08

Note: N = 170; M = mean; SD = standard deviation

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Staff

Fellow

Doctoral Student

Student

User

Question 2: "Sometimes people who talk and act differently are treated like they aren’t capable or smart." (N=170)

Strongly Disagree Disagree Neutral Agree Strongly Agree

57

CERN Status – Valuing Differences

As determined by ANOVA (F(4, 165) = 3.26, p= .013), there is a statistically significant

difference between the CERN status regarding the valuing of differences. A Tukey

post hoc test revealed that students support the value of diversity more, as well as

perceive their work environment to do the same. Users have a more neutral percep-

tion.

Table 39: Means and standard deviation for CERN Status: Valuing Differences CERN Status

N

M

SD

Staff

39

3.50

.67

Fellow

33 3.23 .77

Doctoral Student

29 3.27 .72

Student

29 3.68 .55

User

40 3.16 .67

Note: N = 170; M = mean; SD = standard deviation

CERN Status – Work Load

As determined by ANOVA (F(4, 79.63 = 11.47, p= .000), there is a statistically signif-

icant difference between the CERN status groups regarding Work Load. A Tukey post

hoc test revealed four significant differences (all groups are affected): between stu-

dents and staff, between users and staff, between users and fellows and between

students and doctoral students.

Table 40: Means and standard deviation for CERN Status: Work Load CERN Status

N

M

SD

Staff

39

2.88

1.17

Fellow

33 2.77 1.13

Doctoral Student

29 2.96 .97

Student

29 2.21 .79

User

40 3.51 .79

Note: N = 170; M = mean; SD = standard deviation

58

When looking at the means of the groups, it shows, that users generally perceive their

work load to be very high and agree with the notion to be overwhelmed by work (M =

3.51). Looking at the answers to questions 23 (Figure 10): “I feel like I am given more

work than I can reasonably handle”, there was no user who strongly disagreed with

that statement, while 45% of users agree (Figure 9). Doctoral students are ranked

second when looking at high work loads (M = 2.96). Students on the other hand dis-

agree and perceive their work load not to be very high (M = 2.96). Fellows and staff

have a neutral attitude towards their work load.

Figure 10: Detailed results for question 23 (Work Load): CERN Status

CERN Status – Trust

As determined by ANOVA (F(4, 165) = .701, p= .592), there is no statistically signifi-

cant difference between the CERN status regarding trust towards the organisation.

Table 41: Means and standard deviation for CERN Status: Trust CERN Status

N

M

SD

Staff

39

3.42

.57

Fellow

33 3.33 .71

Doctoral Student

29 3.23 .68

Student

29 3.48 .73

User

40 3.45 .58

Note: N = 170; M = mean; SD = standard deviation

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Staff

Fellow

Doctoral Student

Student

User

Question 23: I feel like I am given more work than I can reasonably handle.

Strongly Disagree Disagree Neutral Agree Strongly Agree

59

CERN Status – Affirmative-Action Group Perception

As determined by ANOVA (F(4, 165) = 2.38, p= .54) there is no statistically significant

difference between the CERN status groups regarding affirmative-action initiatives.

Table 42: Means and standard deviation for CERN Status: Affirmative-Action Group Per-ception

CERN Status

N

M

SD

Staff

39

3.20

.73

Fellow

33 2.92 .71

Doctoral Student

29 3.23 .75

Student

29 2.90 .74

User

40 3.34 .76

Note: N = 170; M = mean; SD = standard deviation

CERN Status – Adaptation

As determined by ANOVA (F(4, 165) = .702 p= .59) there is no statistically significant

difference between the CERN status regarding Adaptation.

Table 43: Means and standard deviation for CERN Status: Adaptation CERN Status

N

M

SD

Staff

39

3.98

.45

Fellow

33 3.85 .55

Doctoral Student

29 4.00 .49

Student

29 3.88 .56

User

40 4.00 .43

Note: N = 170; M = mean; SD = standard deviation

CERN Status – Sensitivity/Flexibility

As determined by ANOVA (F(4, 165) = .823 p= .51) there is no statistically significant

difference between the CERN status regarding Sensitivity/ Flexibility.

60

Table 44: Means and standard deviation for CERN Status: Sensitivity/Flexibility CERN Status

N

M

SD

Staff

39

2.94

.61

Fellow

33 2.87 .75

Doctoral Student

29 3.00 .70

Student

29 2.99 .66

User

40 3.14 .62

Note: N = 170; M = mean; SD = standard deviation

5.3.6 Summary of the results

Table 45 shows a summary of the results of the data analysis and testing of the five

hypotheses. It can be stated that despite the generally neutral perception of the di-

versity climate at CERN, there are some significant differences within the population.

Differences for five demographic variables were predicted. For the variables of gen-

eration (age) and the level of managerial responsibilities no differences could be

found.

The most differences in perception could be identified between men and women. Men

perceive the inclusion of cultural groups and individuals who are different more posi-

tively. They also perceive their work environment more welcoming to differences than

women. Women on the other hand are more open to affirmative-action initiatives and

to adapting to people who are different in their work environment. However, men also

show a clear confirmative attitude towards adapting to people who are different.

For the dimension Cultural Group Inclusion, which measures the perception of minor-

ity social identity groups being marginalized, the only difference that could be de-

tected was for gender. When it comes to nationality and generation, there was no

different perception between minority and majority groups, which indicates a positive

diversity climate.

61

When it comes to affirmative-action initiatives, the prediction that minority groups view

them more positively (as often being the targeted group), than majority groups, has

been proved correct along the dimension of nationality and gender.

Looking at the CERN status, students have a more positive view on the inclusiveness

at CERN as well as the valuing of differences. Furthermore, supervisors, users and

doctoral students report a higher work load than the rest of the CERN population.

62

Table 45: Summary of results of data analysis

Group Difference: Status at CERN

M H1 Group Differ-ence: Gender

H2 Group Difference: Nationality

H4 Group Difference: Generation

H3 Level of managerial responsibilities

H5 CERN Status

Cultural Group Inclusion

2.62 Male perception more positive

None None None students more positive perception than users and doctoral students

Organisational Inclusion

2.54 Male perception more positive

None None None None

Valuing Differences

3.35 Male perception more positive

None None None students more positive perception than users

Work load 2.94 None None None supervisors more negative perception

users and doctoral stu-dents more negative per-ception than students and fellows

Trust 3.37 None None None None None

Affirmative- Action Group Perception

3.11 Female perception more positive

Non-Europeans more positive perception

None None None

Adaptation 3.94 Female perception more positive

None None None None

Sensitivity/ Flexibility

2.98 Female perception less positive

Non-Europeans less positive perception

None None None

63

6 Discussion and recommendations

The results of this non-representative sample of the CERN population show, that

there is a positive diversity climate at CERN, with some different group perceptions

mostly when it comes to gender. Men as the majority group at CERN have a more

positive view especially on inclusiveness at the organisation than women do. This

result is not surprising taking into account that women are traditionally underrepre-

sented in the male dominated field of SET (Science, Engineering and Technology).

The results of the study suggest that training initiatives aimed at raising awareness

on the implications of gender diversity could have a valuable impact on the diver-

sity climate at the organisation. Taking into account that gender diversity is the

origin of the current programme and still a main target of the CERN Diversity Office,

a continuation of this strategy is recommended.

The results show that there are differences in the perception of work load. Super-

visors, as well as users and doctoral students report a higher work load than the

rest of the CERN population. This can have a negative impact on the diversity

climate, because a heavy work load can lead to a lower disposition to pay attention

to and embracing different working styles. A peculiarity of the structure of CERN

is, that users, as the biggest population group at CERN is not employed by the

organisation. The performance appraisal system and control of the work load

therefore lies with another institute. However, the offer of trainings for e.g. time

management for the whole population is an option to address this issue.

As managers were also identified to report a heavier work load, initiatives to sup-

port supervisors in their managerial responsibilities are recommended. The sup-

port of and by management is an important aspect of a successfully implemented

diversity strategy in general: “Senior managers must support diversity initiatives

and must be willing to commit sufficient resources to the effort. Managers must

recognize that effectively implementing workplace diversity requires sustained

commitment to organisational change” (Kreitz et al. 2008). Therefore, support of

employees with managerial responsibilities through transparent processes, time

management trainings, but also personal support and work load monitoring can

aid the successful implementation of diversity initiatives. A targeted training for

64

managers at the organisation is also recommended to take into account leadership

implications of managing a diverse workforce.

CERN has in place general training initiatives, as a stand-alone offer, as well as

part of other trainings e.g. in recruitment. In addition to these, informal training

offers are recommended to be implemented, as e.g. suggested by Harrison et al.

(2000): “Provide opportunities for employees to experience interactions with di-

verse others”. The researchers added the factor of time and frequency of interac-

tions to their studies of collaboration in diverse teams. They suggest that regular

interactions with people of a different demographic group can reduce the negative

bias and increase the probability of effective collaboration. In the subscale Sensi-

tivity/Flexibility, differences were indicated between gender and nationality groups.

Regular interactions could influence the perception of minority groups as being

characterized as out-groups positively.

Even though training is an important part of diversity management, the setup of

processes, structures and reward mechanisms is also essential for a positive di-

versity climate. On a team level, this could take the form of collective appraisal

systems. Harrison et al. (2000) suggest “that when members’ individual outcomes

depend more on team performance, they collaborate more frequently” (ibid.: 27).

Measures to enhance team building can be beneficial for the diversity climate of

an organisation. As Hofhuis et al. (2011: 966) proposed, when employees not only

identify with groups based on demographic characteristics, but simultaneously with

the organisation, they display a dual identity, strengthening the trust in the organi-

sation. The results of the survey suggest a neutral attitude when it comes to trust

toward the organisation, which can be influenced positively by building a stronger

relationship with the organisation by supporting team building.

65

7 Discussion of methodology

It is appropriate to point out some limitations of this study and the survey that

should be addressed in future research.

First of all, this study was conducted with a convenience sample, involving a Fa-

cebook group and the network of the researcher. This method targeted a certain

age group. The question therefore arises, whether the sample is representative of

the organisation. As shown in chapter 4.4, the demographics of the CERN popu-

lation differ significantly from the sample demographics. Further insight into a pop-

ulation that might have been underrepresented, could be provided by conducting

interviews with a selection of CERN employees. Due to time constraints, the re-

searcher refrained from conducting interviews.

Furthermore, throughout this survey the term diversity was used to include a vari-

ety of dimensions: cultural diversity, gender diversity, age diversity, disability etc.

However, when questioning individual perceptions, the different types of diversity

should be specified, as different ideas and issues are connected to them. This was

especially problematic, since the ODNA was originally used to test cultural diversity

(Dahm 2009: 283), and marginally age and gender diversity. For the purpose of

this study, the wording was adapted to include a broader definition of diversity.

However, the problem arising is the assumption that heterogeneous groups face

the same interactional issues. To gain more detailed knowledge about the diversity

climate and differences of perception the adaptation of the questions to a specific

type of diversity and its interactional implications is recommended.

Moreover, the ODNA was developed in the USA, which implicates different as-

pects due to the specific historical and political context. For example, the question-

naire subscale “Affirmative-Action Group Perception” has especially political impli-

cations in the USA, the origin of such initiatives, where it has a negative reputation.

In a population which consists mainly of Europeans other relevant subscales might

be identified.

In the analysis groups were defined as minority groups, based on an overall com-

parison to the population. This was for example the case for women. However, in

their immediate work environment, this might not be the case.

66

In addition, when questioning the perception of a sample group, the results are

based on self-reflexivity. Bias regarding group-identity, favorable self-concept and

preferred social traits could influence the results of the study (Tajfel, Turner 1979).

Furthermore, there is an issue in coherence of the subscales of the ODNA. The

subscale Valuing Differences questions whether differences are evaluated posi-

tively, which thus contributes to a positive diversity climate. At the same time, the

subscale Sensitivity/Flexibility indicates a negative outcome, when minority groups

are perceived as different, as an “out-group”. The researcher tried to get in contact

with Prof. Dahm to request more detailed information on the subscales than pub-

licly available, but was not successful. When applying the ODNA again however,

it is desirable to gain additional knowledge on the theory behind the subscales,

than given in Dahm 2009.

As for the forming of the independent variables, the nationalities were grouped into

European and Non-European to ensure sufficient sized sample groups. However,

the group of Non-Europeans is very heterogeneous. For further research a more

detailed division of this sample group should be considered.

This research was based on the assumption that surface-level diversity such as

gender, age and nationality determines the attitude of the employee towards diver-

sity. However, as explained in chapter 2.4, it was suggested that deep-level diver-

sity, meaning the value structures of the individual is more significant. After con-

firming that there are some dimensions for which the perceptions are equal, a fu-

ture research should correlate diversity perceptions with an assessment of individ-

ual value structures, in order to get a better insight into employees’ perception.

Another issue to be taken into account for future research, is the age of the re-

search on which the literature review is based. Many of the used articles are over

20 years old: “Factors related to time are important in assessing research applica-

bility - earlier findings may not be relevant to today’s workplace.” (Tschirhart, Wise

2000: 392). There is numerous research and a fast development in the area of

diversity management. Therefore, the paradigm under which it is evaluated and

analysed is shifting rapidly. An example is the evolvement of the ODNA itself: It is

based on a survey by Larkey (1996) and adapted to the context of the early 21.

Century.

67

8 Tables and Figures Figures

Figure 1: Gender distribution of sample and CERN population .................................. 28 Figure 2: Composition of survey respondents and CERN population: Generation (Age) 30 Figure 3: Composition of survey respondents and CERN population: CERN Status .. 31 Figure 4: Detailed results for question 2 (Cultural Group Inclusion): Gender .............. 38 Figure 5: Detailed results for question 8 (Organisational Inclusion): Gender ............... 39 Figure 6: Detailed results for question 15 (Valuing Differences): Gender .................... 40 Figure 7: Detailed results for question 40 (Adaptation): Gender .................................. 42 Figure 8: Detailed results for question 45 (Sensitivity/Flexibility): Nationality .............. 46

Figure 9: Detailed results of question 2 (Cultural Group Inclusion): CERN Status ...... 56 Figure 10: Detailed results for question 23 (Work Load): CERN Status ...................... 58

Tables

Table 1: Sample and independent variables ................................................................ 28 Table 2: Descriptive Statistics and correlations of the eight dimensions and overall diver-sity climate ................................................................................................................... 34 Table 3: Means and standard deviation for women and men: Cultural Group Inclusion 37 Table 4: Means and standard deviation for women and men: Organisational Inclusion 38 Table 5: Means and standard deviation for women and men: Valuing Differences ..... 39 Table 6: Means and standard deviation for women and men: Work load .................... 40 Table 7: Means and standard deviation for women and men: Trust ............................ 40

68

Table 8: Means and standard deviation for women and men: Affirmative-Action Group Perception .................................................................................................................... 41 Table 9: Means and standard deviation for women and men: Adaptation ................... 41 Table 10: Means and standard deviation for Europeans and Non-Europeans: Sensitiv-ity/Flexibility .................................................................................................................. 42 Table 11: Means and standard deviation for Europeans and Non-Europeans: Cultural Group Inclusion ............................................................................................................ 43 Table 12: Means and standard deviation for Europeans and Non-Europeans: Organisa-tional Inclusion ............................................................................................................. 43 Table 13: Means and standard deviation for Europeans and Non-Europeans: Valuing Dif-ferences ....................................................................................................................... 44 Table 14: Means and standard deviation for Europeans and Non-Europeans: Work Load..44 Table 15: Means and standard deviation for Europeans and Non-Europeans: Trust .. 45 Table 16: Means and standard deviation for Europeans and Non-Europeans: Affirmative-Action Group Perception .............................................................................................. 45 Table 17: Means and standard deviation for Europeans and Non-Europeans: Adapta-tion.46 Table 18: Means and standard deviation for Europeans and Non-Europeans: Sensitiv-ity/Flexibility .................................................................................................................. 46 Table 19: Means and standard deviation for people with and without managerial respon-sibilities: Cultural Group Inclusion ............................................................................... 47 Table 20: Means and standard deviation for people with and without managerial respon-sibilities: Organisational Inclusion ............................................................................... 48 Table 21: Means and standard deviation for people with and without managerial respon-sibilities: Valuing Differences ....................................................................................... 48 Table 22: Means and standard deviation for people with and without managerial respon-sibilities: Work load ..................................................................................................... 49 Table 23: Means and standard deviation for people with and without managerial respon-sibilities: Trust .............................................................................................................. 49

69

Table 24: Means and standard deviation for people with and without managerial respon-sibilities: Affirmative-Action Group Perception ............................................................. 49 Table 25: Means and standard deviation for people with and without managerial respon-sibilities: Adaptation ..................................................................................................... 50 Table 26: Means and standard deviation for people with and without managerial respon-sibilities: Sensitivity/Flexibility ...................................................................................... 50 Table 27: ANOVA for eight dimensions: Generation (Age) .......................................... 51 Table 28: Means and standard deviation for the generational groups: Cultural Group In-clusion ......................................................................................................................... 51 Table 29: Means and standard deviation for the generational groups: Organisational In-clusion .......................................................................................................................... 52 Table 30: Means and standard deviation for the generational groups: Valuing Differ-ences...52 Table 31: Means and standard deviation for the generational groups: Work Load ...... 52 Table 32: Means and standard deviation for the generational groups: Trust ............... 53 Table 33: Means and standard deviation for the generational groups: Affirmative-Action Group Perception ......................................................................................................... 53 Table 34: Means and standard deviation for the generational groups: Adaptation ...... 54 Table 35: Means and standard deviation for the generational groups: Sensitivity/Flexibil-ity..54 Table 36: ANOVA for eight dimensions: CERN Status ................................................ 55 Table 37: Means and standard deviation for CERN Status: Cultural Group Inclusion . 55 Table 38: Means and standard deviation for CERN Status: Organisational Inclusion . 56 Table 39: Means and standard deviation for CERN Status: Valuing Differences ........ 57 Table 40: Means and standard deviation for CERN Status: Work Load ...................... 57 Table 41: Means and standard deviation for CERN Status: Trust ............................... 58

70

Table 42: Means and standard deviation for CERN Status: Affirmative-Action Group Per-ception ......................................................................................................................... 59 Table 43: Means and standard deviation for CERN Status: Adaptation ...................... 59 Table 44: Means and standard deviation for CERN Status: Sensitivity/Flexibility ....... 60 Table 45: Summary of results of data analysis ............................................................ 62 Table 46: Cronbach’s α for all eight dimensions .......................................................... 88 Table 47: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Cultural Group Inclusion ..................................................................................... 89 Table 48: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Organisational Inclusion ..................................................................................... 89 Table 49: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Valuing Differences ............................................................................................ 90 Table 50: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Work Load .......................................................................................................... 90 Table 51: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Trust ................................................................................................................... 91 Table 52: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Affirmative-Action Group Perception .................................................................. 91 Table 53: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Adaptation .......................................................................................................... 92 Table 54: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Sensitivity/Flexibility ........................................................................................... 92 Table 55: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Cultural Group Inclusion ........................................................... 93 Table 56: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Organisational Inclusion ............................................................ 93 Table 57: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Valuing Differences ................................................................... 94 Table 58: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Work Load ................................................................................. 94

71

Table 59: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Trust ........................................................................................... 95 Table 60: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Affirmative-Action Group Perception.......................................... 95 Table 61: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Adaptation .................................................................................. 96 Table 62: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Sensitivity/Flexibility ................................................................... 96 Table 63: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Cultural Group Inclusion .................................................................... 97 Table 64: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Organisational Inclusion ..................................................................... 97 Table 65: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Valuing Differences ............................................................................ 98 Table 66: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Work Load .......................................................................................... 98 Table 67: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Trust .................................................................................................. 99 Table 68: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Affirmative-Action Group Perception .................................................. 99 Table 69: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Adaptation ......................................................................................... 99 Table 70: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Sensitivity/Flexibility ........................................................................... 100 Table71: Equality of variances for 8 dimensions: Generation (Age) ............................ 100 Table 72: Equality of variances for 8 dimensions: CERN Status ................................. 102  

72

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77

ANNEX 1 Map of CERN Member States as of March 2016

Member States: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Israel, Italy, Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland, United Kingdom (Source: http://international-relations.web.cern.ch/International-Relations/ms/; access: 17.05.2016)

78

ANNEX 2

Action Points of CERN Diversity Programme

STRATEGIC OBJECTIVES  ACTIONS 

RECRUITMENT 

# 1 

Improve the distribution of under‐represented national‐ities through  proactive measures in sourcing and pre‐selection, with “excel‐lence”  remaining the  over‐arching criterion 

Reinforce efforts to widen the applicant  pool in sourcing and shortlisting stages 

Monitor to maintain progress and  redress 

anomalies 

Develop further contacts to attract more appli‐

cants through enhanced outreach activities 

# 2 

Achieve optimal gender

distribution in recruit‐

ment for all  professional 

categories, with “excel‐

lence” remaining the 

over‐arching criterion 

Reinforce efforts to achieve gender  distribution 

in sourcing and shortlisting stages 

Monitor to maintain progress and  redress 

anomalies 

Explore ways of assuring temporary  solutions for 

maternity leave cover 

CAREER DE‐

VELOPMENT  # 3 

Provide more gender role mod‐

els 

Succession planning (m/w) 

Leadership training (m/w) 

Coaching and mentoring (m/w) 

# 4 

Propose parallel career 

development opportuni‐

ties (technical and mana‐

gerial paths in parallel) 

Align advancement criteria 

Provide development planning –  technical or 

managerial as appropriate 

WORK ENVI‐

RONMENT  # 5  Promote the exchange of ideas 

and  understanding  between generations  and professions 

Workshops within departments, sectors or CERN‐wide – facilitated  discussions on specific themes  related to Organisation life 

# 6 

Explore ways to improve 

work/life  balance 

Assess the necessity of e‐mail/meetings  outside 

of working hours – enhance  awareness of the 

possible impact within  hierarchical relationships 

Support requests for part‐time work, SLS  and teleworking, in line with  individual and service needs 

# 7 

Promote a work environ‐ment based on mutual respect and  inclusiveness 

Design and deliver events to raise  awareness and exchange experiences  of diversity in the workplace 

Assure regular communication 

Continually improve support  structures such as 

reserved places in  local crèches, kindergartens, 

etc., in  line with needs 

Ensure access and equipment as needed for 

disabled individuals 

Source: CERN Diversity Programme Activity Report 2012-2015 (restricted access)

79

ANNEX 3

The original Organisational Diversity Need Analysis (ODNA) Answer options: Strongly agree – Agree – Neutral – Disagree - Strongly disagree Organisational Inclusion

- It seems that the real reason people are denied promotions or raises is that they are seen as not fitting in.

- It’s hard to get ahead here unless you are part of the “old boys’ network”. - When it comes to getting support for getting ahead here, I feel like I have

fallen through the cracks. - I have to prove myself more and work a lot harder to get into that next posi-

tion because of my gender or nationality. - Performance evaluations seem to be biased against those who are different

because supervisors focus on very traditional ways of getting things done. - Whenever I‘ve confronted someone for giving me a hard time because of

my nationality or gender, they have denied the problem or played it down. - I feel I have been treated differently here because of my nationality, gender

or age. Cultural Group Inclusion

- Some people in our team are “talked down to” because they are different. - Sometimes people who talk and act differently are treated like they aren’t

capable or smart. - There are people in our team who have a hard time accepting ideas when

they are offered by someone who is different from them. - When people begin working on a problem from a very different perspective

they have a hard time seeing each other‘s point of view. - When people from different backgrounds work together in groups, some

people feel ignored because their ideas are not acknowledged. - People get ahead by using “pull” and not because of what they know. - Diversity issues keep some teams here from performing to their maximum

effectiveness. Valuing differences

- When people have a different orientation or style, they take the time to ex-plain and try to understand the other person‘s point of view.

- When people in our team take the offense or miscommunicate they sit down and talk about the differences until they understand each other.

- Employees share their knowledge/expertise with other employees regard-less of their gender or nationality.

80

- We all seem to learn and grow from our differences. - When someone is timid or reluctant to assert their ideas, others will point it

out and ask for their opinion. - People in our team don‘t notice culture or gender differences since we are

really all the same. - Peoples‘ habits or ways of thinking may be different because of their back-

ground, but when it comes to working, we‘re pretty much all the same. Work Load

- The amount of work I have makes me feel extremely stressed at the end of the day.

- I feel like I am given more work than I can reasonably handle. - My workload is so heavy that I feel like I can‘t possibly finish during an ordi-

nary workday. - The amount of work I have interferes with how well I can do my job.

Affirmative-Action Group Perceptions

- Women, minorities and older people are more likely to get promoted and get ahead now.

- Women, minorities and older people don‘t adjust their style to fit the busi-ness context.

- People are sometimes hired for a job with less qualifications than other ap-plicants because they are minorities or women.

- Members of some nationality have a unique way of acting in workgroups which makes them stand out as being different.

- Sometimes women, and minorities and older people should be given special consideration in hiring and promotions.

- Women, minorities and older people don‘t have the same employment op-portunities as others have.

Trust

- People of the same nationality or gender tend to look out for each other. - With many people, you don‘t know how you stand. - If I were having difficulties, I know members of my group would try to help

me out. - I can trust people I work with to lend me a hand if I need it. - I feel confident that my company will always try to treat me fairly. - My company is sincere in its attempts to understand the employee‘s point

of view. Adaptation

- I feel like it‘s up to me to adjust to others when their nationality or gender presents differences in styles or mannerisms.

81

- Working with employees with different backgrounds forces me to reconsider how I approach things.

- I go out of my way to learn about others‘ cultural backgrounds, traditions and points of view.

- Knowing more about the cultural norms of diverse groups would help me to be more effective in my job.

- I think that diverse viewpoints add value. - I can enjoy being with people whose culture, gender or age is very different

from mine. - I believe women, minorities and older people should adopt the values and

lifestyle of the dominant culture. Sensitivity/Flexibility

- It seems that minorities and women have a special sensitivity and under-standing of diversity issues.

- Women and minorities are better able to value the different ways of looking at things and doing work than white males.

- Women and minorities often interpret things differently than white males. - Women and minorities use the diverse backgrounds of others to help with

group problem-solving. - Women and minorities often encourage others to express their opinion. - It seems that minorities and women are more likely to adjust their styles of

work when necessary. - It seems that women and minorities express more empathy for others than

white males.

82

ANNEX 4

Questionnaire introduction text Link: http://kristin-dev.web.cern.ch/survey I am currently a Fellow in the CERN Diversity Office and at the same time com-pleting a Master's degree in Intercultural Communication Studies. For my Master thesis, I am researching the diversity climate at CERN, using the Organisational Diversity Needs Analysis (ODNA), a questionnaire which is a validated instrument in social science to measure diversity awareness. It was used at universities, com-panies as well as public institutions. I’m using it now to measure your perception of diversity at CERN. I'm looking for people who have been at CERN for at least 4 months in the past year. Your support by filling out the survey is much appreciated. It should not take you more than 15 minutes to complete. I kindly ask you to com-plete the survey by 10 March 2016.

The research carried out is "personal/academic" and not related to CERN's diver-sity initiatives, although I am receiving support from CERN through access to doc-uments and data. The information you provide will be treated anonymously. Con-fidentiality is guaranteed and only the global results will serve as a source of infor-mation to the CERN Diversity Office, not individual replies. The data you provide will not be used by any other service of the CERN Human Resources Department. The questionnaire covers the following dimensions: organisational inclusion, cul-tural group inclusion, the value of differences, work load, trust, affirmative-action, adaptation and sensitivity. If you have any comments or questions that you would like to address, please don't hesitate to get in touch with me: kristin.kaltenhauser@cern.ch Kristin

83

ANNEX 5

The Questionnaire – CERN version Link: http://kristin-dev.web.cern.ch/diversity-survey Have you been at CERN for at least four months in the last year?

- Yes - No

Following questions have been posed to rate on a 5-item Likert scale: ● Strongly disagree ● Disagree ● Neutral ● Agree ● Strongly agree I. Cultural Group Inclusion/Exclusion Explanation: Think about the people you work with regularly, particularly those you consider to be your team at CERN. Please respond by indicating how much you agree or disagree with each statement as it relates to your experience in the team you work with, particularly when you are at CERN.

1. Some people in our team are “talked down to” by their colleagues because they are different.

2. Sometimes people who talk and act differently are treated like they aren’t capable or smart.

3. There are people in our team who have a hard time accepting ideas when they are offered by someone who is different from them.

4. When people begin working on a problem from a very different perspective they have a hard time seeing each other‘s point of view.

5. When people from different backgrounds work together in groups, some people feel ignored because their ideas are not acknowledged.

6. People get ahead by being persuasive and not because of what they know. 7. Diversity issues keep some teams at CERN from performing to their maxi-

mum effectiveness. II. Organisational Inclusion/Exclusion Explanation: Please select "N/A" if not applicable.

8. It seems that the real reason people are denied promotions or raises is that they are seen as not fitting in.

84

9. It’s hard to get ahead at CERN unless you are part of the “old boys’ net-work”.

10. When it comes to getting support for getting ahead at CERN, I feel like I have been overlooked.

11. I have to prove myself more and work a lot harder to get into that next posi-tion because of my gender, nationality, sexual orientation, belief or disabil-ity.

12. Performance evaluations seem to be biased against those who are different because supervisors focus on very traditional ways of getting things done.

13. Whenever I‘ve confronted someone for giving me a hard time because of my gender, nationality, sexual orientation, belief or disability, they have de-nied the problem or played it down.

14. I feel I have been treated differently at CERN because of my gender, na-tionality, sexual orientation, belief or disability.

III. Valuing Differences

15. When people have a different orientation or style, they take the time to ex-plain and try to understand the other person‘s point of view.

16. When people in our team take offense or miscommunicate, they sit down and talk about the differences until they understand each other.

17. Colleagues share their knowledge/expertise with other colleagues regard-less of their nationality, gender, belief, sexual orientation or physical ability.

18. We all seem to learn and grow from our differences. 19. When someone is timid or reluctant to assert their ideas, others will point it

out and ask for their opinion. 20. People in our team don‘t notice differences related to nationality, gender,

belief or sexual orientation since we are really all the same. 21. People's habits or ways of thinking may be different because of their back-

ground, but when it comes to working, we‘re pretty much all the same. IV. Work Load

22. The amount of work I have makes me feel extremely stressed at the end of the day.

23. I feel like I am given more work than I can reasonably handle. 24. My workload is so heavy that I feel like I can‘t possibly finish during an ordi-

nary workday. 25. The amount of work I have interferes with how well I can do my job.

85

V. Trust

26. People of the same nationality, gender, belief or sexual orientation tend to look out for each other.

27. With many people, you don‘t know where you stand. (removed after Cronbach’s α test)

28. If I were having difficulties, I know members of my team would try to help me out.

29. I can trust people I work with to lend me a hand if I need it. 30. I feel confident that CERN will always try to treat me fairly. 31. CERN is sincere in its attempts to understand the employee‘s point of view.

VI. Affirmative-Action Group Perception Explanation: The term minority is used here along the following dimensions: na-tionality, gender, belief, sexual orientation and physical ability.

32. Minorities are more likely to get promoted and get ahead now. 33. Minorities don‘t adjust their style to fit the business context. (removed after

Cronbach’s α test) 34. People are sometimes hired for a job with less qualifications than other ap-

plicants because they are minorities. 35. Members of some nationality have a unique way of acting in workgroups

which makes them stand out as being different. (removed after Cronbach’s α test)

36. Sometimes minorities should be given special consideration in hiring and promotions.

37. Minorities don‘t have the same employment opportunities as others have. VII. Adaptation Explanation: The term minority is used here along the following dimensions: na-tionality, gender, belief, sexual orientation and physical ability.

38. I feel like it‘s up to me to adjust to others when e.g. their nationality or gender presents differences in styles or mannerisms.

39. Working with colleagues with different backgrounds forces me to reconsider how I approach things.

40. I go out of my way to learn about others‘ cultural backgrounds, traditions and points of view.

41. Knowing more about the cultural norms of diverse groups would help me to be more effective in my job.

42. I think that diverse viewpoints add value. 43. I can enjoy being with people whose culture, gender, belief or sexual orien-

tation is very different from mine.

86

44. I believe minorities should adopt the values and lifestyle of the dominant culture.

VIII. Sensitivity/Flexibility Explanation: The term minority is used here along the following dimensions: na-tionality, gender, belief, sexual orientation and physical ability.

45. It seems that minorities have a special sensitivity and understanding of di-versity issues.

46. Minorities are better able to value the different ways of looking at things and doing work than most others.

47. Minorities often interpret things differently than most others. 48. Minorities use the diverse backgrounds of others to help with group prob-

lem-solving. 49. Minorities often encourage others to express their opinion. 50. It seems that minorities are more likely to adjust their styles of work when

necessary. 51. It seems that minorities express more empathy for others than most others.

Demographics Age:

- Under 18 - 18-25 - 26-35 - 36-45 - 46-55 - 56-65 - Over 65

I identify my gender as…

- Female - Male - Trans*

Nationality (Dropdown list) Status at CERN (Dropdown list) Department

87

(Dropdown list) Do you feel part of a minority at CERN, other than related to your gender or na-tionality (e.g. sexual orientation, physical ability, belief, etc.)? - Yes (If you want, please specify) - No Do you have supervisory responsibilities at CERN? - Yes - No Are you interested to participate in a one-on-one interview with the researcher? - Yes - No - Maybe Thank you for participating in this research project! Feel free to use this area for comments, concerning this questionnaire or how you feel about diversity in your team or at CERN.

88

ANNEX 6

Cronbach’s α for all eight dimensions

Table 46: Cronbach’s α for all eight dimensions

Subscale Number of

items Cronbach's

α Deleted items

Cronbach's α af-ter deletion

Cultural Group Inclusion

7 0.908* - -

Organisational Inclusion

7 0.914* - -

Valuing Differences

7 0.789* - -

Work load

4 0.913* - -

Trust

6 (5) 0.403* Q27 0.693*

Affirmative-action Group Perception

6 (4) 0.353 Q33, Q37 0.634*

Adaptation

7 0.664* - -

Sensitivity/Flexibility

7 0.866* - -

* p > 0.6

89

ANNEX 7 Results for test of Equality of variances, t-test and ANOVA for all independent variables and dimensions A7.1 Results for eight dimensions: H1 Gender A7.1.1 Gender – Cultural Group Inclusion Table 47: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Cultural Group Inclusion

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .282 .596 3.318*** 181 .001 .188 .741

Not assu-med

3.305 174.321 .001 .187 .742

Note: N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

The table shows that the assumption of equal variances was not violated. The

significance level for Levene’s test was .60, which is larger than the cut-off at .05;

therefore equal variances were assumed.

A7.1.2 Gender – Organisational Inclusion  Table 48: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Organisational Inclusion

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.542 .216 3.293*** 181 .001 .187 .748

Not assu-med

3.264 169.073 .001 .185 .751

Note. N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

In the table, it was noted that the assumption of equal variances had not been

violated because the significance level for Levene’s test was .22, which is larger

than the cut-off of .05; therefore, equal variances were assumed.

90

A7.1.3 Gender – Valuing differences Table 49: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Valuing Differences

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.356 .246 -3.104* 181 .002 -.510 -.113

Not assu-med

-3.079 170.017 .002 -.511 -.111

Note. N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

The data supports the assumption of equal variances because the significance

level for Levene’s test was .25, which is larger than the cut-off at .05.

A7.1.4 Gender – Work Load Table 50: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Work Load

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .007 .932 .522 181 .602 -.235 .405

Not assu-med

.522 177.408 .602 -.235 .405

Note. N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

The table proves that the assumption of equal variances was not violated because

the significance level for Levene’s test was .93, which is larger than the cut-off at

.05; therefore, equal variances were assumed.

91

A7.1.5 Gender – Trust Table 51: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Trust

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .009 .926 -.602 181 .548 -.244 -.130

Not assu-med

-.606 180.683 .545 -.242 -.128

Note: N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

Equal variances were assumed because the significance level for Levene’s test

was .93 (p > .05).

A7.1.6 Gender – Affirmative-Action Group Perception Table 52: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Affirmative-Action Group Perception

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .002 .961 2.503* 181 .013 .057 .485

Not assu-med

2.506 178.166 .013 .057 .485

Note: N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

The assumption of equal variances was not violated because the significance level

for Levene’s test was .96 (p > .05)

92

A7.1.7 Gender – Adaptation Table 53: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Adaptation

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 5.899 .016 3.067 181 .002 .077 .358

Not assu-med

3.141* 174.198 .002 .081 .355

Note: N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

The data does not support the assumption of equal variances because the signifi-

cance level for Levene’s test was .02, which is smaller than the cut-off at .05.

Therefore unequal variances were assumed and the Welch correction was applied.

A7.1.8 Gender – Sensitivity/ Flexibility Table 54: Equality of variances (Levene’s) and Mean (independent t-test) for women and men: Sensitivity/Flexibility

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .000 .986 2.976* 181 .003 .098 .485

Not assu-med

2.984 178.984 .003 .098 .484

Note: N = 183. CI = confidence interval; df = degrees of freedom.

*p < .05. *** p <.001.

Equal variances were assumed because the significance level for Levene’s test

was .99 (p > .05).

93

A7.2. Results for eight dimensions: H2 Nationality A7.2.1 Nationality – Cultural Group Inclusion Table 55: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Cultural Group Inclusion

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .048 .826 1.813 181 .072 -.031 .739

Not assu-med

1.698 37.230 .098 -.068 .776

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

Equal variances were assumed because the significance level for Levene’s test

was .83 which is larger than the cut-off at .05.

A7.2.2 Nationality – Organisational Inclusion Table 56: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Organisational Inclusion

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .445 .506 .144 181 .886 -.365 .423

Not assu-med

36.440 .897 -.416 .474

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001. 

The data in the above table supports the assumption of equal variances because

the significance level for Levene’s test was .51 (p > .05)

94

A7.2.3 Nationality – Valuing Differences Table 57: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Valuing Differences

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.923 .167 -1.623 181 .106 -.503 .048

Not assu-med

-1.409 35.290 .168 -.554 .100

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

Equal variances were assumed because the significance level for Levene’s test

was .17, which is larger than the cut-off at .05.

A7.2.4 Nationality – Work Load Table 58: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Work Load

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .811 .369 1.768 181 .079 -.04508 .82307

Not assu-med

1.900 42.104 .064 -.02412 .80211

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001. The data shows that the assumption of equal variances was not violated because

the significance level for Levene’s test was .37, which is larger than the cut-off at

.05.

95

A7.2.5 Nationality – Trust

Table 59: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Trust

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.450 .230 .407 181 .685 -.203 .308

Not assu-med

.351 35.75 .727 -.252 .357

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001. Equal variances were assumed because the significance level for Levene’s test

was .23 (p > .05).

A7.2.6 Nationality – Affirmative-Action Group Perception

Table 60: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Affirmative-Action Group Perception

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.184 .278 2.983* 181 .003 .148 .729

Not assu-med

3.509 46.810 .001 .187 .690

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001. The table demonstrates that the assumption of equal variances was not violated

because the significance level for Levene’s test was .28 (p > .05).

96

A7.2.7 Nationality - Adaptation

Table 61: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Adaptation

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.021 .314 1.307 181 .193 -.066 .325

Not assu-med

1.504 45.530 .139 -.043 .303

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001. The data supports the assumption of equal variances because the significance

level for Levene’s test was .31 (p > .05) 

A7.2.8 Nationality – Sensitivity/ Flexibility

Table 62: Equality of variances (Levene’s) and Mean (independent t-test) for Europeans and Non-Europeans: Sensitivity/Flexibility

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.139 .287 2.003* 181 .047 .004 .539

Not assu-med

2.217 43.475 .032 .024 .519

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001. Equal variances were assumed because the significance level for Levene’s test

was .29 (p > .05).

97

A7.3. Results for eight dimensions: H3 Managerial responsibilities

A7.3.1 Managerial responsibilities – Cultural Group Inclusion

Table 63: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Cultural Group Inclusion

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .047 .829 -.953 181 .342 -.503 .175

Not assu-med

-.938 63.410 .352 -.513 .185

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

The table shows that the assumption of equal variances was not violated. The

significance level for Levene’s test was .83, which is larger than the cut-off at .05.

A7.3.2 Managerial responsibilities – Organisational Inclusion

Table 64: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Organisational Inclusion

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 1.477 .226 -.736 181 .463 -.473 .216

Not assu-med

-.669 57.383 .506 -.513 .256

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

The table demonstrates that the assumption of equal variances was not violated

because the significance level for Levene’s test was .23 (p > .05).

98

A7.3.3 Managerial responsibilities – Valuing Differences

Table 65: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Valuing Differences

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .249 .618 .018 181 .986 -.241 .246

Not assu-med

.018 62.884 .986 -.250 .254

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

The data in the above table supports the assumption of equal variances because

the significance level for Levene’s test was .62, which is larger than the cut-off at

.05.

A7.3.4 Managerial responsibilities – Work Load

Table 66: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Work Load

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .065 .798 -2.46* 181 .015 -.847 -.093

Not assu-med

-2.54 68.220 .013 -.839 -.101

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

The above table proves that the assumption of equal variances was not violated

because the significance level for Levene’s test was .80, which is larger than the

cut-off at .05, therefore, equal variances were assumed.

99

A7.3.5 Managerial responsibilities – Trust

Table 67: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Trust

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 2.04 .155 -.458 181 .647 -.276 .172

Not assu-med

-.533 84.299 .596 -.246 .142

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

Equal variances can be assumed because the significance level for Levene’s test

was .16 (p > .05).

A7.3.6 Managerial responsibilities – Affirmative-Action Group Perception

Table 68: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Affirmative-Action Group Perception

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 2.78 .097 -.262 181 .793 -.295 .225

Not assu-med

-.290 76.431 .773 -.272 .203

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

The above table demonstrates that the assumption of equal variances was not

violated because the significance level for Levene’s test was .10 (p > .05).

A7.3.7 Managerial responsibilities – Adaptation

Table 69: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Adaptation

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed 3.31 .070 -.082 181 .935 -.179 .165

Not assu-med

-.096 85.980 .923 -.154 .140

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

100

The data in above table supports the assumption of equal variances because the

significance level for Levene’s test was .07 (p > .05).

A7.3.8 Managerial responsibilities – Sensitivity/Flexibility

Table 70: Equality of variances (Levene’s) and Mean (independent t-test) for managerial responsibilities: Sensitivity/Flexibility

95% CI

Equal vari-ances

F Sig. t df p Lower Upper

Assumed .020 .888 -.759 181 .935 -.327 .145

Not assu-med

-.772 66.552 .923 -.326 .144

Note: N = 183. CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

Equal variances were assumed because the significance level for Levene’s test

was .89 (p > .05).

A7.4. Results for eight dimensions: H4 Generation (Age)

Table71: Equality of variances for 8 dimensions: Generation (Age)

Levene‘s statistic

df1

df2

Sig. 95 % CI

Lower Upper

Cultural Group Inclu-sion

.557

2

179

.574

2.477 2.762

Organisational Inclu-sion

.005 2 179 .995 2.40 2.69

Valuing Differences .524 2 179 .593 3.25 3.45 Work Load 1.188 2 179 .307 2.78 3.10 Trust .255 2 179 .775 3.27 3.45 Affirmative-Action Group Perception

.369 2 179 .692 3.00 3.22

Adaptation .442 2 179 .643 3.86 4.01 Sensitivity/Flexibility .143 2 179 .867 2.88 3.08

Note: N = 182; CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

101

A7.4.1 Generation (Age) – Cultural Group Inclusion

The assumption of equal variances was not violated because the significance level

for Levene’s test was .57 (p > .05).

A7.4.2 Generation (Age) – Organisational Inclusion

Equal variances were assumed because the significance level for Levene’s test

was .99 (p > .05).

A7.4.3 Generation (Age) – Valuing Differences

The assumption of equal variances was not violated because the significance level

for Levene’s test was .59 (p > .05).

A7.4.4 Generation (Age) – Work Load

The assumption of equal variances was not violated because the significance level

for Levene’s test was .31 (p > .05).

A7.4.5 Generation (Age) – Trust

The assumption of equal variances was not violated because the significance level

for Levene’s test was .78 (p > .05).

A7.4.6 Generation (Age) – Affirmative-Action Group Perception

The assumption of equal variances was not violated because the significance level

for Levene’s test was .69 (p > .05).

A7.4.7 Generation (Age) – Adaptation

The assumption of equal variances was not violated because the significance level

for Levene’s test was .64 (p > .05).

A7.4.8 Generation (Age) – Sensitivity/Flexibility

The assumption of equal variances was not violated because the significance level

for Levene’s test was .87 (p > .05).

102

A7.5. Results for eight dimensions: H5 CERN Status

Table 72: Equality of variances for 8 dimensions: CERN Status

Levene‘s statistic

df1

df2

Sig. 95 % CI

Lower Upper

Cultural Group In-clusion

.527

4

165

.716

2.48

2.78

Organisational In-clusion

.189

4

165

.944

2.38

2.68

Valuing Diffe-rences

.992 4 165 .413 3.25 3.46

Work Load 3.77 4 165 .006* 2.74 3.06 Trust .652 4 165 .626 3.28 3.48 Affirmative-Action Group Perception

.255 4 165 .906 3.01 3.24

Adaptation .63 4 165 .645 3.87 4.02 Sensitivity/Flexibi-lity

.68 4 165 .605 2.89 3.09

Note: N = 170; CI = confidence interval; df = degrees of freedom. *p < .05. *** p <.001.

A7.5.1 CERN Status – Cultural Group Inclusion

The assumption of equal variances was not violated because the significance level

for Levene’s test was .72 (p > .05).

A7.5.2 CERN Status – Organisational Inclusion

The assumption of equal variances was not violated because the significance level

for Levene’s test was .94 (p > .05).

A7.5.3 CERN Status – Valuing Differences

The assumption of equal variances was not violated because the significance level

for Levene’s test was .41 (p > .05).

A7.5.4 CERN Status – Work Load

The assumption of equal variances was violated because the significance level for

Levene’s test was .006, which is smaller than the cut-off at .05. Therefore unequal

variances are assumed and the Welch correction is applied.

103

A7.5.5 CERN Status – Trust

The assumption of equal variances was not violated because the significance level

for Levene’s test was .63 (p > .05).

A7.5.6 CERN Status – Affirmative-Action Group Perception

The assumption of equal variances was not violated because the significance level

for Levene’s test was .91 (p > .05).

A7.5.7 CERN Status – Adaptation

The assumption of equal variances was not violated because the significance level

for Levene’s test was .65 (p > .05).

A7.5.8 CERN Status – Sensitivity/Flexibility

The assumption of equal variances was not violated because the significance level

for Levene’s test was .61 (p > .05).

104

Declaration of Originality

I declare herewith, that this thesis paper is my own original work. Furthermore, I

confirm that:

− this work has been composed by me;

− I have clearly referenced all sources used in the work;

− all data and findings in the work have not been falsified or embellished;

− this work has not been previously, or concurrently, used either for other

courses or as an exam work;

− this work has not been published before.

I understand that any false claim in respect of this work will result in failure of this

assessment due to plagiarism.

……………………………………………………

Erfurt, 18 July 2016