Abstract

Generalizability in qualitative research has been a controversial topic given that interpretivist

scholars have resisted the dominant role and mandate of the positivist tradition within social

sciences. Aiming to find universal laws, the positivist paradigm has made generalizability a

crucial criterion for evaluating the rigor of quantitative research. This positivist echo has led

generalizability to acquire a quantitative meaning, inappropriate for describing qualitative

studies. The purpose of qualitative research has thus been directed towards providing in-

depth explanations and meanings rather than generalizing findings. Through a critical review

of empirical and theoretical studies, this commentary seeks to show that in qualitative

domains generalizability is possible provided that: first, generalizability is the main objective

of the study; second, due precautions concerning the philosophy and terminology selected are

taken. Hence, this commentary contributes to the literature on qualitative research by making

suggestions for more consistent and unanimous procedures to adopt in qualitative inquiries.

Keywords: qualitative and quantitative research, positivist and interpretivist tradition,

probabilistic generalizability, theoretical generalizability, transferability

1

Generalizability in Qualitative Research:

A Tale of Two Traditions

‘In one word, to draw the rule from experience, one must generalize:

This is a necessity that imposes itself on the most circumspect observer’

― Henri Poincaré

Between the 1970s and the early 1990s, advancements in computer technology facilitated the

processing of large data sets in quantitative studies (Morse, 2008; Ormston, Spencer, Barnard

& Snape, 2014). This fact, together with the increased interest of evidence-based decision

making in medical and health fields in the 1980s, and a widespread diffusion of the

systematic review methodology in scientific research (Bradt, 2009), has made generalizability

of findings, already a valued standard for decades, a pivotal criterion for evaluating the

excellence of quantitative research (Polit & Beck, 2010).

Since then, researchers in the qualitative tradition have begun to pay greater attention

to discussions on the feasibility of generalization in qualitative studies (Flyvbjerg, 2001).

However, this feasibility of generalizing findings could be seen as a “phantom”, as an

“illusion”, for qualitative scholars (Groleau, Zelkowitz and Cabral, 2009, p. 417). Indeed,

without due precautions and clarifications, the nature of interpretivist paradigm, relying on a

different logic to the positivist paradigm, could make generalizability almost an unachievable

aim in qualitative research (Morse, 2008).

Trying to define the thorny and illusive concept of generalizability may represent a

challenge to researchers because of the ambiguity and polyhedral meanings associated with it

(Polit & Beck, 2010). Simply put, the act of generalizing involves forming general and broad

statements from specific cases (Schwandt, 2001), which also means that inferences about

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what cannot be observed are made on the basis of what can be observed (Polit & Beck,

2010). Defined in this way, the notion of generalizability has neither a quantitative nor a

qualitative dimension per se, but it has, instead, a neutral and impartial connotation.

Nevertheless, the dominant role of the positivist tradition in social sciences has led

generalizability to acquire a more quantitative nature (Kerlinger & Lee, 2000). Thus,

generalizability has become almost inherently associated with quantitative research and its

focus on finding universal laws and statistical generalizations (Delmar, 2010). Consequently,

due to this positivist echo, the application of the same concept of generalizability to

qualitative perspectives, grounded in an interpretivist paradigm, has become rather

controversial (Polit & Beck, 2010). As a result, generalizability in qualitative studies has

often been misunderstood and disregarded in favor of the more common purpose of providing

in-depth understanding of the specific topics under research (Ayres, Kavanagh, & Knafl,

2003).

However, dismissing a priori the ability to generalize from qualitative studies on the

bases of biased premises due to ‘quantitative contamination’ can significantly limit the

strength and beauty of qualitative research, especially in the eyes of early-career researchers.

A clear conceptualization of the meanings associated with the concept of generalizability in

qualitative research is needed, taking into account both methodological and philosophical

boundaries.

Therefore, this commentary aims to show that even in qualitative domains

generalizability is possible provided two paramount conditions exist. First, generalizability is

the main objective of the study. Second, due precautions related to the terminology selected

are taken into considerations. Concerning these due precautions, on the one hand, if

researchers want to preserve the term generalizability in qualitative enquiries, the

philosophical traditions underpinning the research have to be clearly specified. In so doing,

3

the kind of generalizability that can be attained, namely analytical/theoretical, and the type of

knowledge that can be pursued in qualitative research would be straightforward and

unequivocal. On the other hand, if new terms were to be introduced, a suitable vocabulary

should be unanimously shared by all qualitative scholars to unmistakably describe quality in

qualitative enquiries. Hence, this commentary contributes to the literature on qualitative

research approaches by making suggestions on those paramount conditions which may lead

to more consistent and unanimous procedures to describe and elaborate qualitative research.

The commentary unfolds in four main parts. In the first part, after providing a brief

definition of the term, the value of generalizability within the positivist tradition is analyzed.

The second part investigates the nature of generalizability in qualitative approaches in light of

interpretivist perspectives. In the third part, an example of a theory-generating research

method, i.e. grounded theory, within the interpretivist tradition is outlined. The last part

tackles two main precautions researchers should take when conducting qualitative

investigations. This last part specifically proposes the adoption of the notion of contextual

knowledge as ‘phronesis’ and the diffusion of a terminology for qualitative research

universally approved by the scientific community. Recommendations and the conclusion

close the commentary.

Generalizability in the Positivist, Quantitative Tradition

The positivist tradition in social sciences has strongly polarized the notion of generalizability

and influenced the terminology in scientific research (Flyvbjerg, 2001; Ormston et al., 2014).

Since the Enlightenment, natural sciences, which are nomothetic by essence (Thomae, 1999),

have indisputably dominated Western culture, drawing attention to instrumental rationality

and the focus on generalizable and context-independent theories (Falk, Rocha & Warnick,

2009). In an effort to emulate natural science (Flyvbjerg, 2001), the positivist tradition in

social sciences, which traces back to philosophers such as Comte, Hume and Bacon, has

4

argued and acknowledged the possibility of reaching one, monolithic truth (Lee &

Baskerville, 2003). Positivism assumes that “scientific knowledge is the paradigm of valid

knowledge” (Larrain, 1979, p. 197) and, as such, authentic knowledge can be verified

through empirical evidence, which is in turn interpreted through reason and logic (Macionis

& Gerber, 2010).

Consequently, the ultimate aim of quantitative research defined by the positivist

tradition is to produce laws able to explain and govern every observed phenomenon and to

determine a universal knowledge (Delmar, 2010) that holds true, and is invariable in, all

places and at all times (Falk et al., 2009). In this sense, as Morse (2008) has underlined,

generalizability is at the heart of usefulness. Hence, by assuming an impartial and objective

researcher’s involvement (Winter, 2000) to limit any possible forms of influence in the

research process (Davies & Dodd, 2002), quantitative experimental methods have been

employed to test hypotheses and infer generalizable conclusions (Dingwal, Murphy, Watson,

Greatbatch & Parker, 1998; Hoepfl, 1997).

These generalizable conclusions stem from a research process based on

methodological rigor. Rigor in the positivist tradition refers to the soundness, exactitude and

accuracy of a study in regard to its planning, data collection, analysis, and reporting

(Marquat, 2017). The assessment of objective scores, such as reliable and valid

measurements, are indicators of such exactitude, so that results from one study can be

replicated in other studies and then generalized (Claydon, 2015).

Results in quantitative research can be generalized through probabilistic

generalization (Polit & Beck, 2010), which is based on randomly selected samples

representative of the population (Lee & Baskerville, 2003). Although some authors have

claimed that convenience sampling bias could hamper the validity of findings in many studies

(Gheondea-Eladi, 2014), statistical generalizability remains a crucial tenet and a prerogative

5

in quantitative approaches (Winter, 2000). This probabilistic generalization is also termed

external validity (Gheondea-Eladi, 2014). External validity, together with internal validity,

namely the degree to which it is possible to infer causality between two variables (Bryman,

Becker & Sempik, 2008; Joppe, 2000) and reliability, which describes the extent to which

results are consistent over time and accurately represent the total population (Bryman et al.,

2008; Joppe, 2000), is a paramount criterion for evaluating quality in quantitative studies

(Gheondea-Eladi, 2014; Polit & Beck, 2010).

As a result, generalizability has become associated with the notion of external

validity, which represents only a specific aspect of the original term, namely probabilistic

generalizability (Flyvbjerg, 2001; Lee & Baskerville, 2003). Hence, generalizability has been

pulled towards the positivist approaches and their quantitative influence has been instilled. It

is no surprise that when the term generalizability is mentioned, statistical generalization is the

first notion to come into one’s mind, as if synonymous with it.

Generalizability in the Interpretivist, Qualitative Tradition

The highlighted importance of the word generalizability in quantitative studies has led many

qualitative scholars to question the possibility of generalizing results from qualitative

research (Davies & Dodd, 2002) and, consequently, ponder on how to judge its quality

(Hallberg, 2013). As Ormston et al. (2014) have underlined, qualitative approaches in social

sciences have started to emerge as recent phenomena alongside the widespread diffusion of

sophisticated statistical methods, which were framed within positivist principles to imitate

natural sciences methodology.

Nonetheless, the philosophical tradition behind qualitative research, drawing from

authors such as Weber, Kant and Dilthey is the interpretivist paradigm (Bryman et al., 2008;

Morse, Barrett, Mayan, Olson & Spiers, 2002) and, in an antipodal way to the positivist

perspective, is idiographic in nature (Thomae, 1999). Interpretivism prioritizes the

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understanding of human behaviour over the prediction and generalization of causes and

effects (Macionis & Gerber, 2010).

As such, the strength of qualitative inquiries defined by the interpretivist tradition is

the understanding of how individuals, through their narratives, perceive and experience their

lives, constructing meanings within their social and cultural contexts (Groleau et al., 2009;

Mishler, 2000). In this sense, interpretivist research emphasizes the hermeneutics and

perception of the social world, as well as the interactions between individuals and the

surrounding context (Ormston et al., 2014). It follows that findings are intrinsically linked to

the research context and that the interfacial distance between the researcher and the

researched is minimized (Davies & Dodd, 2002).

Consequently, the researcher is an agentic instrument for collecting and analyzing

data and an essential tool for actively constructing concepts (Hallberg, 2013). Thus, by using

either theoretical or non-probabilistic samples (Gheondea-Eladi, 2014), qualitative studies

aim to explore meanings and processes of people’s everyday lives to gain an in-depth

understanding of situations and actions (Groleau et al., 2009; Hallberg, 2013). Because of this

stress on values and subjective meanings, qualitative research has often been criticized as

being relativistic, soft or unscientific compared to quantitative enquiries (Ormston et al.,

2014).

To avoid this subordinated position, the same standards used to judge quality in

quantitative research have been transposed and employed to evaluate quality in qualitative

studies (Delmar, 2010), so that generalizability has become a rather pivotal matter even in an

area where it is beset by indistinctness (Delmar, 2010; Golafshani, 2003). In fact, this osmotic

transfer has raised numerous issues related to its fundamental inadequacy in depicting the

true nature of qualitative research processes and aims (Kitto, Chesters & Grbich, 2008).

Winter has stated that “qualitative research sets itself up for failure when it attempts to follow

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established procedures of quantitative research” (2000, pp. 11). Indeed, by doing so,

interpretivist social sciences have accepted terms that are by nature self-defeating (Flyvbjerg,

2001).

As a result, the importance of generalization of results in the qualitative field has been

frequently dismissed, considered unattainable or irrelevant (Kitto et al., 2008) and not the

purpose of quality enquiries (Morse, 1999). Researchers have thus preferred to invert their

focus to the other fundamental aim of qualitative studies, which is to engage in research able

to produce thorough descriptions as well as a deep, rich and contextualized understanding of

human experience (Polit & Beck, 2010).

However, (1) if the purpose of a study and its research questions aim to build a new

theory to bridge a gap in the literature (Gheondea-Eladi, 2014) or (2) if due precautions of the

conceptualization of generalizability are respected (Hallberg, 2013), then discussing

generalizability of findings even in qualitative research makes sense (Delmar, 2010; Krefting,

1991; Morse, 1999; Polit & Beck, 2010; Winter, 2000). The following two sections expand

on these two paramount conditions to clarify generalization in the interpretivist paradigm.

Grounded Theory, a Theory-Generating Research Method

With regard to the first point of building a new theory, within the many different qualitative

methods (Krefting, 1991), theory-generating procedures seek to generalize findings

(Eisenhardt, 1989; Glaser & Strauss, 1967; Hallberg, 2013; Ormston et al., 2014). An

example of these theory-generating procedures is grounded theory (Eisenhardt, 1989; Glaser

& Strauss, 1967; Corbin & Strauss, 2008). Although the aim of this commentary is far

beyond providing an exhaustive description of grounded theory, some key features of this

theory-generating method are now discussed to provide evidence and strength to the

argument that generalizability is achievable also in qualitative research. This is feasible since

the purpose of grounded theory is to inductively construct a general theory that is able to

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answer the research question in the absence or incompleteness of alternative existing

frameworks (Gheondea-Eladi, 2014).

Starting from thick descriptions and then going beyond through to high levels of

abstraction (Goulding, 2002), grounded theory develops an iterative process based on four

main steps, namely coding, conceptualization, classification and categorization, to build a

substantiated theory (Gheondea-Eladi, 2014). After this first theoretical result, the research is

replicated in other settings so that several other substantiated theories can be yielded

(Goulding, 2002). Indeed, as Firestone (1993) has noted, replication in different conditions

reinforces generalizability in qualitative investigations, since consistency of results when

conditions vary indicates that findings are robust. This also explains the reason why extreme

cases, those that due to their extreme characteristics accentuate the dynamics being

investigated facilitating the emergence of the aspects of interest (Eisenhardt, 1989) are so

critical for enhancing qualitative research (Polit &Beck, 2010).

When every observation has been incorporated and no unexplained variance has been

left out, then saturation is reached (Dingwall, Murphy, Watson, Greatbatch & Parker, 1998).

Saturation implies that sufficient and redundant information for all aspects of the

phenomenon under research has been gathered (Morse et al., 2002) and thus no further

themes or concepts can emerge (Glaser & Strauss, 1967). At this point, a formal, final theory

can be elaborated (Corbin & Strauss, 2008).

The formulation of a new theory is possible due to the action of abstracting the

‘general’ from the ‘particular’ in terms of similarities and differences in individuals and

circumstances (Delmar, 2010). From this perspective, the power of generalization of the final

theory not only depends on the researcher’s thorough immersion and engagement with the

data (Polit & Beck, 2010), but also on the intensity of within-case and across-case analyses

(Ayres et al., 2003). As Morse has argued, “if qualitative research was considered not

9

generalizable, then it would be of little use, insignificant and hardly worth doing” (1999, p.

5). Hence, there would be a high risk of falling into an endemic relativism (Davies & Dodd,

2002). Nevertheless, as grounded theory has shown, generalizability of findings in qualitative

studies is possible: it is simply a different kind of generalizability compared to that of

quantitative research (Polit & Beck, 2010). It is an analytic, or theoretical, form of

generalization.

Due Precautions in Qualitative Investigations

Given the fact that research undertaken in the interpretivist tradition can aim for theoretical

generalizability, How are researchers able to avoid confusion when using such an ambiguous

and misused term? What can be done to properly describe qualitative studies, releasing them

from the pervasive influence of positivist perspectives?

First Precaution

The first due precaution is related to the fact that if researchers want to preserve the term

generalizability within the qualitative enquiries, then the interpretivist paradigm should be

clearly specified at the beginning of a study (Hallberg, 2013). Stating the philosophical

tradition underpinning a research determines the kind of generalizability, i.e.

analytical/theoretical, that can be obtained and pursued and prevents misunderstandings

(Hallberg, 2013). In this sense, by recognizing and acknowledging the existence of this other

specific form of generalization, the quantitative meaning can be balanced out and the

originally neutral connotation of the broad term restored. Restoring the neutral connotation of

the term generalizability emphasizes the view that generalizability in social sciences can

never be certain (Polit & Beck, 2010).

Because of the focus on and importance of the context, interactions and hermeneutics,

the aim of the interpretivist tradition is to predict a theoretical understanding of the topic

10

under examination (Yin, 1994). As such, results are not reached through statistical procedures

or other means of quantifications (Corbin & Strauss, 2008), and generalization is interpreted

as generalization towards a theory, rather than towards the population (Polit & Beck, 2010).

This is why the notion of sample size in relation to generalizability is rather

controversial in qualitative investigations (Malterud, Siersma & Guassora, 2016). On the one

hand, sample sizes may be too large to permit a deep and detailed analysis, on the other too

small to support claims of having achieved either theoretical saturation or information

redundancy (Boddy, 2016). Additionally, data saturation and information redundancy are

elusive concepts and no clear explanations of how they should be understood or implemented

to justify the number of participants exist (Morse, 1995). Although recently some guidelines

have been proposed to determine “information power” (Malterud et al., 2016), defining the

adequate sample size in qualitative research is ultimately a matter of the researcher’s

experience and judgment of the quality of the data collected and the research method

employed (Buddy, 2016).

Thus, generalizability in qualitative studies is focused on the researcher’s analysis and

understanding of circumstances rather than on the collection of representative data (Delmar,

2010; Morse, 1999). In this sense, generalization entails inferring the potential extrapolations,

or transferability, of those results on the basis of both a theoretical analysis of the aspects

generating the outcomes and the effects of the context (Eisenhardt, 1989; Yin, 1994).

Such contextual effects are crucial in qualitative enquiries. Since they seek to

understand phenomena unfolding naturally in specific environments (Patton, 2002), declaring

the philosophical tradition underpinning a study also has an impact on the type of knowledge

that can be acquired. Within the philosophical tradition of interpretivism, a theory which

pertains only to the setting in which it was developed would not detract from its scientific

status nor would it prohibit researchers from extending that theory to additional settings (Lee

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& Baskerville, 2003). On the contrary, what may work for people in a certain circumstance is

likely to work for other people placed in a similar situation (Hallberg, 2013; Hyde, 2000).

Therefore, since qualitative understanding relies on a comprehensive knowledge of

the case and its nuances in each specific context (Hyde, 2000), talking about ‘situated’

knowledge rather than epistemological knowledge would then be more appropriate (Davies &

Dodd, 2002; Haraway, 1988). As such, as Flyvbjerg (2001) has suggested, it would be

interesting to introduce the Aristotelian concept of phronesis, value-based, context-dependent

knowledge. Words such as episteme -pure knowledge- and techne -applied knowledge- have

informed the current language (i.e. epistemology, technic, technology). Whilst episteme

indicates generalizable-across-settings knowledge, usually called science, techne refers to

practical, specific knowledge. However, occurrences of the word phronesis, which sits

between episteme and techne, and encompasses both scientific and technical knowledge by

adding values, experiences, context and reflexivity, do not exist in the present language

(Flyvbjerg, 2001).

It follows that the idea according to which true knowledge is only that which can be

replicated in different places and times has to be rejected. Instead, context-dependent

knowledge, with its different modes of expression, can offer a likewise true understanding,

but in another form in terms of its replicability and applicability (Delmar, 2010). Thus, in the

interpretivist tradition of social science, for which the constant interaction between human

agents and the surrounding context is essential, it would be more suitable to talk about

‘phronetic knowledge’ (Flyvbjerg, 2001). Because of the link with the setting, a context-

dependent knowledge would do justice to the essence of qualitative enquiries and their

conceptualization of generalizability.

Second Precaution

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The second precaution is related to the introduction of new terms. It refers to some qualitative

scholars’ plea to select a novel and unanimously accepted vocabulary to better indicate the

principles underpinning qualitative approaches and evaluate their quality (Agar, 1986;

Golafshani, 2003; Seale, 1999). Quality is in fact a hallmark of every piece of research

(Hallberg, 2013), and “each paradigm should be judged by its own paradigm’s terms”

(Golafshani, 2003, p. 601). This calls into question the use of term generalizability itself.

Some researchers, echoing Shakespeare’s ‘What's in a name?’i (Romeo & Juliet, Act

II, Scene II, v. 47), have argued that the positivist terminology, such as the headings

‘reliability’, ‘validity’ and ‘rigor’, could be still used in interpretivist qualitative research and

just redefined in terms of meaning (Guba & Lincoln, 1981; Morse et al., 2002). For instance,

whilst reliability could indicate the “negotiation of truths through a series of subjective

accounts”, validity could reside “with the representation of the actors, the purposes of the

research and appropriateness of the processes involved” (Winter, 2000, pp. 9-10).

Nonetheless, some new labels have also been proposed to cut ties with the positivist

tradition and underline the independent identity of the interpretivist perspective (Agar, 1986).

Indeed, qualitative research often breaks with and challenges many of the tenets of so-called

good quantitative research, as it is the case with the notion of reliability and validity (Davies

& Dodd, 2002; Golafshani, 2003). Hence, a plethora of alternative concepts have arisen to

mark the initially moderate and then radical paradigm shift (Seale, 1999) and an alternative

terminology, able to express qualitative connotations, has been supported. For example, the

word trustworthiness could be considered as an alternative to the qualitative term for rigor

(Davies & Dodd, 2002; Morse, 2002). Trustworthiness has been proposed and initially

defined by Guba and Lincoln (1981) through four criteria: truth value (corresponding to

quantitative internal validity), applicability (quantitative external validity or generalizability),

13

consistency (quantitative reliability) and neutrality (quantitative researcher’s objectivity and

distance).

To relate this term even more closely to the interpretivist tradition, the same authors

have further modified the four-point list of criteria (Lincoln & Guba, 1985). This modified

and well-established model comprises concepts such as credibility (prior truth value -

quantitative internal validity), transferability (prior applicability - quantitative external

validity or generalizability), dependability (prior consistency - quantitative reliability) and

confirmability (prior neutrality - quantitative researcher’s objectivity and distance) (Lincoln

& Guba, 1985). In subsequent seminal works, Guba and Lincoln (1989; 1994) also

introduced the notion of authenticity, to represent a range of multiple realities and truths in

line with the interpretivist perspective. In line with this alternative terminology,

transferability should be used and preferred in qualitative research instead of theoretical

generalizability.

However, even if the original aim of the changes in the terminology was to bring

clarity and a universally acknowledged terminology in the field, these guidelines still lack

shared agreement between academics (Morse, 2002). A bewildering proliferation of new

terms has hindered the selection of a vocabulary unanimously accepted by scholars (Seale,

1999). The absence of a recognized canon, through which to appropriately evaluate the

quality and trustworthiness of the study may be one of the reasons for the skepticism

surrounding generalizability in qualitative research (Delmar, 2010).

Nevertheless, whilst this burgeoning terminology reflects the difficulties and

contradictions that qualitative methodologists have met in developing an overarching system

for specifying quality (Seale, 1999), it also represents an essential first step towards defining

the autonomous status of qualitative research (Morse, 2002). These criteria are in fact

fundamental to judge the rigor or, better, trustworthiness and attentiveness of qualitative

14

inquiries because they are a watershed between ‘good’ and ‘bad’ quality research (Davies &

Dodd, 2002). Trustworthiness is built through the transparency, reflexivity and accuracy of

the research practice itself and the credibility, and genuineness of a qualitative study depends

mainly on the researcher’s ability and effort to unfold and explain interactions (Golafshani,

2003; Thorne & Darbyshire, 2009).

Hence, a thorough and exhaustive explanation of these processes should be able to

provide high-quality qualitative works (Golafshani, 2003). In this sense, by reflecting valid

and rich descriptions of sufficient depth, the research findings warrant a degree of

generalizability (Thorne & Darbyshire, 2009), or, following the well-established criteria

(Golafshani, 2003; Shenton, 2004) proposed by Lincoln and Guba (1985), transferability.

Transferability becomes possible thanks to the agentic role of the reader. As final recipient

and arbiter, and thanks to the thick details of the phenomena under investigation provided by

the author (Delmar, 2010), the reader can justify the extrapolation and application of the

findings to other settings and situations, thus making transferability inferences (Shenton,

2004). In so doing, a final and solid knowledge is confirmed and approved by the research

community (Delmar, 2010).

Implications and Conclusion

The aim of this commentary has been to show that qualitative studies, besides providing an

in-depth understanding of contextualized human experience, may also pursue theoretical

generalizability or, more pertinent for qualitative approaches, transferability, as outlined by

Lincoln and Guba (1985). This purpose can be achieved depending on two circumstances:

first, generalization of results has to be the aim of the research and implemented method;

second, terminological precautions have to be taken.

Regarding terminological precautions, on the one hand, if researchers want to make

use of the term generalizability, a first precaution would suggest that the philosophical roots

15

underpinning a study are briefly declared at the beginning of that study (Hallberg, 2013).

Given the variety of philosophical approaches, providing details on the author’s specific

philosophical orientation would help clarify the kind of generalizability, i.e.

analytical/theoretical, that can be drawn from the findings, avoiding potential future

misinterpretations. This may also have an impact on the specific knowledge that can be

acquired in social sciences (Flyvbjerg, 2001). Since this major category of academic

disciplines deals with the unpredictable and ever-changing human subject, the importance of

the context, especially in the interpretivist tradition, is paramount to defying the dynamics

surrounding the role of the researcher, the participants, the corpus of data, the analysis and

the general interpretations of their emerging interrelationships. As such, a contextual

knowledge, which could be called phronetic knowledge, is as fundamental as a more

positivist epistemological knowledge.

On the other hand, the second precaution concerns the use of a new terminology,

symbol of a paradigm shift, more suitable and consistent with the interpretivist philosophical

tradition of qualitative enquiries. To be efficient and effective, the community of scholars

should unanimously agree on and adopt an adequate, recognized and unambiguous

vocabulary to accurately describe their findings, their own role in the study and the research

process as a whole. Although variety and creativity also play an important role in qualitative

research, a shared terminological canon may facilitate the evaluation of the excellence and

trustworthiness of qualitative studies.

In so doing, the commentary has contributed to the literature on qualitative research

approaches by making suggestions for more consistent and common procedures in qualitative

inquiries. Indeed, introducing precise guidelines may enhance the clarity of qualitative

investigations and give more justice to the importance and beauty of such research. This

would also spur researchers who have just started their research journey traditions not to

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dismiss qualitative research as less scientific, but, instead, to better appreciate the inherent

differences between two opposite philosophical approaches.

From a more practical point of view, appreciating such differences would recognize

the massive contribution of qualitative research to the understanding of real world problems

and phenomena. This is particularly evident, for instance, when considering decision-making

issues in the crucial field of medicine and health, as well as in business, marketing and ethics

problems. Qualitative research explores individuals’ perceptions and feelings about those

processes and dynamics underpinning decision making, accessing areas not amenable to

quantitative research (Pope & Mays, 1995). In this sense, they are also prerequisite and thus

complementary to good quantitative research (Pope & Mays, 1995). As Albert Einstein has

famously stated “Everybody is a genius. But if you judge a fish by its ability to climb a tree,

it will live its whole life believing that it is stupid”.

17

References

Ayres, L., Kavanagh, K. & Knafl, K. (2003). Within-case and across-case approaches

to qualitative data analysis. Qualitative Health Research, 13, 871-883.

doi:10.4135/9781412985895

Boddy, C. R. (2016). Sample size for qualitative research. Qualitative Market

Research: An International Journal, 19(4), 426-432. doi:10.1108/qmr-06-2016-0053

Bradt, D. A. (2009). Evidence-based decision-making (part 1): Origins and evolution

in the health sciences. Prehospital and Disaster Medicine, 24, 298-305.

Bryman, A., Becker, S. & Sempik, J. (2008). Quality criteria for quantitative,

qualitative and mixed methods research: A view from social policy. International Journal of

Social Research Methodology, 11, 261-276. doi:10.1080/13645570701401644

Claydon, L. S. (2015). Rigour in quantitative research. Nursing Standard, 29(47), 43-

48. Doi:10.7748/ns.29.47.43.e8820

Corbin, J. & Strauss, A. (2008). Basics of qualitative research (3rd ed.): Procedures

and techniques for developing grounded theory. Thousand Oaks, CA: Sage Publications.

doi:10.4135/9781452230153

Davies, D. & Dodd, J. (2002). Qualitative research and the question of rigor,

Qualitative Health Research, 12, 279-289. doi:10.1177/104973230201200211

Delmar, C. (2010). “Generalizability” as Recognition: Reflections on a Foundational

Problem in Qualitative Research. Qualitative Studies, 1, 115-128.

Dingwall, R., Murphy, E., Watson, P., Greatbatch, D. and Parker, S. (1998). Catching

goldfish: quality in qualitative research. Journal of Health Services Research and Policy, 3,

167-172. doi:10.1177/135581969800300308

18

Eisenhardt, K. (1989). Building theories from case study research. Academy of

Management Review, 14, 532-550. doi:10.5465/amr.1989.4308385

Falk, T. M., Rocha, S. and Warnick, B. R. (2009). Social science and its discontents:

An essay review of Ben Flyvbjerg’s Making social science matter. Education Review, 12, 1-

16.

Firestone, W. A. (1993). Alternative arguments for generalizing from data as applied

to qualitative research. Educational Researcher, 22, 16-23. doi:10.2307/1177100

Flyvbjerg, B. (2001). Making social science matter: Why social inquiry fails and how

it can succeed again. Cambridge University Press. doi:10.1017/cbo9780511810503

Gheondea-Eladi, A. (2014). Is Qualitative Research Generalizable?. Journal of

Community Positive Practices, 14, 114-124.

Glaser, B. & Strauss, A. (1967). The discovery grounded theory: strategies for

qualitative inquiry, Aldin, Chicago. doi:10.1097/00006199-196807000-00014

Glesne, C. & Peshkin, A. (1992). Becoming qualitative researchers: An introduction.

Longman White Plains, NY. doi:10.3316/qrj0602203

Golafshani, N. (2003). Understanding reliability and validity in qualitative research.

The Qualitative Report, 8, 597-606.

Groleau, D., Zelkowitz, P. & Cabral, I. (2009). Enhancing generalizability: moving

from an intimate to a political voice. Qualitative Health Research, 19, 416-426.

doi:10.1177/1049732308329851

Guba, E. G. & Lincoln, Y.S. (1981). Effective evaluation: Improving the usefulness of

evaluation results through responsive and naturalistic approaches. Jossey-Bass.

19

Guba, E. G. & Lincoln, Y. S. (1989). Fourth Generation Evaluation. Newbury Park,

CA: Sage.

Guba, E. G. & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In

N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of Qualitative Research (pp. 105-117).

Thousand Oaks, CA: Sage.

Hallberg, L. (2013). Quality criteria and generalization of results from qualitative

studies, International Journal of Qualitative Studies on Health and Well-Being, 8, 1.

doi:10.3402/qhw.v8i0.20647

Haraway, D. (1988). Situated knowledge: The science question in feminism and the

privilege of partial perspective. Feminist Studies, 14, 575-599. doi:10.2307/3178066

Hoepfl, M. C. (1997). Choosing qualitative research: A primer for technology

education researchers. Journal of Technology Innovations, 9, 47-63. doi:10.21061/jte.v9i1.a.4

Hyde, K. F. (2000). Recognising deductive processes in qualitative research,

Qualitative Market Research: An International Journal, 3, 82-90.

doi:10.1108/13522750010322089

Joppe, M. (2000). The Research Process. Retrieved February 25, 1998, from

http://www.ryerson.ca/~mjoppe/rp.htm

Kerlinger, F. N. & Lee, H. B. (2000). Foundations of Behavioral Research (4th ed).

Harcourt College Publishers, Fort Worth, TX.

Kitto, S. C., Chesters, J. and Grbich, C. (2008). Quality in qualitative research.

Medical Journal of Australia, 188, 243-246.

Larrain, J. (1979). The Concept of Ideology. London: Hutchinson.

20

Lee, A. S. & Baskerville, R. L. (2003). Generalizing generalizability in information

systems research. Information Systems Research, 14, 221-243.

doi:10.1287/isre.14.3.221.16560

Lincoln, Y. S. & Guba, E. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage.

doi:10.1177/144078338702300329

Macionis, J. & Gerber, L. (2010). Sociology (7th ed.). Don Mills: Pearson Education

Canada.

Malterud, K., Siersma, V. D. & Guassora, A. D. (2016). Sample Size in Qualitative

Interview Studies. Qualitative Health Research, 26(13), 1753-1760.

doi:10.1177/1049732315617444

Marquart, F. (2017). Methodological Rigor in Quantitative Research. The

International Encyclopedia of Communication Research Methods.

Marshall, B., Cardon, P., Poddar, A. & Fontenot, R. (2013). Does sample size matter

in qualitative research?: A review of qualitative interviews in IS research. Journal of

Computer Information Systems, 54(1), 11-22. doi:10.1080/08874417.2013.11645667

Mishler, E. G. (2000). Validation in inquiry-guided research: The role of exemplars in

narrative studies. In B. M. Brizuela, J. P. Stewart, R. G. Carrillo & J. G. Berger (Eds.), Acts

of inquiry in qualitative research (119-146), Cambridge, MA: Harvard Educational Review.

Morse, J. M. (1995). The significance of saturation. Qualitative Health Research,

5(2), 147-149. doi:10.1177/104973239500500201

Morse, J. M. (1999). Qualitative generalizability. Qualitative Health Research, 9, 5-6.

doi:10.1177/104973299129121622

21

Morse, J. M., Barrett, M., Mayan, M., Olson, K. & Spiers, J. (2002). Verification

strategies for establishing reliability and validity in qualitative research, International Journal

of Qualitative Methods, 1, 13-22. doi:10.1177/160940690200100202

Morse, J. M. (2008). “It’s only a qualitative study!” Considering the qualitative

foundations of social sciences. Qualitative Health Research, 18, 147-148.

doi:10.1177/1049732307310262

Ormston, R., Spencer, L., Barnard, M., & Snape, D. (2014). The foundations of

qualitative research. Qualitative research practice: A guide for social science students and

researchers, 2.

Patton, M. Q. (2002). Qualitative evaluation and research methods (3rd ed.).

Thousand Oaks, CA: Sage Publications.

Polit, D. F. & Beck, C. T. (2010). Generalization in quantitative and qualitative

research: Myths and strategies. International Journal of Nursing Studies, 47, 1451-1458.

doi:10.1016/j.ijnurstu.2010.06.004

Pope, C. & Mays, N. (1995). Qualitative research: reaching the parts other methods

cannot reach: an introduction to qualitative methods in health and health services research.

British Medical Journal, 311(6996), 42-45. doi:10.1136/bmj.311.6996.42

Seale, C. (1999). Quality in qualitative research. Qualitative Inquiry, 5, 465-478.

doi:10.1177/107780049900500402

Schwandt, T. A. (2001). Dictionary of qualitative inquiry (2nd ed.). Thousand Oaks,

CA: Sage.

Clark, W. G. (1998). The complete works of William Shakespeare (Vol. 1). Nelson

Doubleday, Incorporated.

22

Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research

projects. Education for Information, 22, 63-75

Thorne, S. & Darbyshire, P., 2005. Land mines in the field: a modest proposal for

improving the craft of qualitative health research. Qualitative Health Research, 15, 1105-

1113. doi:10.1177/1049732305278502

Thomae, H. (1999). The nomothetic-idiographic issue: Some roots and recent

trends. International Journal of Group Tensions, 28(1), 187-215.

doi:10.1023/a:1021891506378

Winter, G. (2000). A comparative discussion of the notion of 'validity' in qualitative

and quantitative research. The Qualitative Report, 4, 1-14.

Yin, R. K. (1994). Case study research. Designs and methods, Thousand Oak: Sage.

23

i “What’s in a name? That which we call a rose by any other name would smell as sweet”, William Shakespeare - Romeo and Juliet, Act II, Scene II, v. 47, (Clark, 1998).