testing the role of schemata in the applicability model of

TESTING THE ROLE OF SCHEMATA IN THE APPLICABILITY MODEL OF

FRAMING EFFECTS: A SURVEY EXPERIMENT ON THE ISSUE OF

BIOTECHNOLOGY

A Thesis

Presented to the Faculty of the Graduate School

of Cornell University

in Partial Fulfillment of the Requirements for the Degree of

Master of Science

by

Yufen Chen

January 2005

ABSTRACT

Researchers have argued that conceptualization of cognitive mechanisms that

underlie framing is vague and have proposed an applicability model to account for

cognitive processes contributing to framing effects (Price & Tewksbury, 1997). The

applicability model assumes the central roles of schema and views framing effects as

applicability effects. In particular, it assumes that media framing will only have an

effect if it resonates with pre-existing schemata held by audience members.

The study described in this thesis tests the applicability model and its

assumption of relevant schemata through a two-by-two experimental design. Through

a national, computer assisted telephone survey of 781 respondents, the study utilizes a

split-ballot technique to measure the effects of two frames (regulation versus non-

regulation) on issues related to biotechnology and genetically modified food products.

A secondary manipulation, varying the order of schemata measures (frame first versus

schema measures first), tests the role of schemata in framing effects. Causal

attributions, attributions of responsibility, and policy opinions are measured as

outcomes of the main manipulation, or framing effects. Additional variables including

demographics, attention to science and technology news across three media, awareness

and support of biotechnology, and ideology were collected to control for and assess

other influences on the outcome variables.

Analyses included independent t-tests to look for differences between the four

experimental groups. Respondents’ schematic strengths were assessed through six

measures. Twelve measures assessed causal attributions, responsibility attributions,

and policy opinions toward regulation of biotechnology.

Results reveal that schemata are directly related to people’s attributions and

opinions on issues related to biotechnology and media attention is directly related to

schema development. In particular, attention to science and technology news on

television, in newspapers, and on the Internet contributed to stronger Information

schemata, which emphasize the importance of science and research in determining the

risks and safety of genetically modified food products. Television was the only

medium that was related to Regulation schemata, which emphasize regulation as a

necessity to protect consumers from the effects of biotechnology and preserve the

environment.

Framing effects occurred across particular schematic strength groups. Two

different schematic groups were more likely to attribute risks associated with

biotechnology to global causes such as the nature of science and information if they

were exposed to the Non-Regulation frame, which emphasized that science and

research should determine if new regulations should be made. Furthermore,

respondents with stronger schemata (medium Regulation and high Information

schematic strength) were more likely to agree with treatment as the cause of risk when

exposed to the Regulation frame, which argued that the FDA must require research and

create regulations to protect citizens from unsafe products. However, differences in

Global attributions were not found across the seven other schematic groups.

Respondents with high Regulation schemas were more likely to attribute

responsibility to the government even when they were exposed to the Non-Regulation

frame. Framing effects were not found for policy opinions and responsibility

attribution to other groups such as non-governmental groups, trade groups and private

corporations, and individuals. These results suggest that schema determine to a large

extent, whether or not framing effects would occur and thus, provide some support for

the Applicability model of framing effects.

Furthermore, interaction effects were found between the main manipulation

(type of frame) and the secondary manipulation (order of schemata measures) for

particular schematic groups. Framing of genetically modified foods influenced policy

opinions for particular schemata groups that were exposed to the schema measures

after the frame manipulation, indicating that the content of schema measures may have

contributed further to framing effects. Question order and possible priming effects are

discussed.

In sum, the results provide limited support for the Applicability model and

demonstrate the need for further research into the cognitive mechanisms that underlie

framing effects. Future study can further illuminate the complexity of audience

schemas and their role in framing effects. Understanding of these cognitive

mechanisms can be used in both development and political communication campaigns,

where message receptibility will depend on audience awareness and schematic

frameworks.

BIOGRAPHICAL SKETCH

Yufen Chen began her graduate training in communication theory and research

at Cornell University in 2002. Prior to graduate school, Yufen worked in advertising

and interactive marketing for five years. She received her Bachelor’s degree from the

State University of New York at Buffalo in 1997 with dual majors in Psychology and

Communication.

iii

ACKNOWLEDGEMENTS

The data for this project was obtained from an annual survey funded by the

Communication Department at Cornell University. Dietram Scheufele, who was the

Chair of my committee and Associate Professor at the Communication Department,

supervised the study. Dr. Scheufele is credited with the idea of using the Luntz report

as the foundation for the design of the frames. This study was not possible without his

initial suggestions on study design and advisement during data collection.

Additionally, I would also like to thank Jim Shanahan, Associate Professor at

the Communication Department, for his comments during the initial design and

proposal stages, as well as Mike Traugott, Associate Professor at the University of

Michigan, for his suggestions on analysis of results.

A paper version of this thesis was submitted to the graduate student paper

competition at the World Association for Public Opinion Research conference and was

awarded the Naomi C. Turner Prize in May, 2004.

iv

TABLE OF CONTENTS

Biographical sketch iii

Acknowledgements iv

Table of Contents v

List of Figures vi

List of Tables vii

Introduction 1

The Concept of Framing 2

The Concept of Schemata 7

Framing and Schemata 11

The Applicability Model of Framing Effects 12

The Current Study 15

Method and Design 19

Analyses and Results 28

Conclusions 42

Discussion 47

Appendix 51

Bibliography 67

v

LIST OF FIGURES

Figure 1 33

Effect of frame on Treatment attribution for respondents

with low Regulation and medium Information schema strength

Figure 2 34

Effect of frame on Global attribution for respondents

with low Regulation and medium Information schema strength

Figure 3 36

Effect of frame on attributions of responsibility to government for respondents

with high Regulation and low Information schema strength

Figure 4 39

Effect of schema order on agreement with Non-regulatory policy for

respondents with low Regulation and low Information schema strength

who were exposed to the Regulation frame

Figure 5 40

Effect of schema order on agreement with Regulatory policy for

respondents with low Regulation and medium Information schema strength

who were exposed to the Non-regulation frame

vi

LIST OF TABLES

Table 1 23

Means and standard deviations for three measures:

attention across three media, awareness, and support to biotechnology

Table 2 24

Two by two experimental design

Table 3

Means and standard deviations for outcome variables 27

Table 4 30

Correlations between media attention, schema development,

awareness, support and perceived risk of biotechnology

Table 5 54

Differences between framed conditions by schema groups

Mean agreement with Global Attribution measures

Table 6 54


Mean agreement with Treatment Attribution measures

vii

Table 7 55


Mean agreement with attributing responsibility to the U.S. government

and federal agencies

Table 8 55


Mean agreement with attributing responsibility to independent,

or non-governmental organizations

Table 9 56


Mean agreement with attributing responsibility to consumers

Table 10 56

Difference between framed conditions by schema groups

Mean agreement with attributing responsibility to private corporations and industry

trade groups

Table 11 57


Mean agreement with Regulation Policies*

viii

Table 12 57


Mean agreement with Information Policies*

Table 13 58

Interactions between the Non-Regulation frame, schema order, and schema strength

Differences between schema order conditions by schema groups, controlling for frame


Table 14 58




Table 15 59



Mean agreement with attributing responsibility to the U.S. government and federal

agencies

Table 16 59



Mean agreement with attributing responsibility to independent, or non-governmental

organizations

ix

Table 17 60




Table 18 60




trade groups

Table 19 61



Mean agreement with Regulation Policies

Table 20 61



Mean agreement with Information Policies

Table 21 62

Interactions between the Regulation frame, schema order, and schema strength



x

Table 22 62




Table 23 63



Mean agreement with attributing responsibility to the U.S. government and federal

agencies

Table 24 63



Mean agreement with attributing responsibility to independent, or non-governmental

organizations

Table 25 64




xi

Table 26 64




trade groups

Table 27 65



Mean agreement with Regulation Policies

Table 28 65



Mean agreement with Information Policies

xii

Introduction

In the report, “Straight Talk,” Frank Luntz presented a set of guidelines for

policy communications to the White House. These recommendations used examples of

environmental communications to contrast Republican and Democratic rhetoric and

stressed the importance of framing and ordering of arguments in addressing any

controversial, public policy issue. Focusing particularly on issues related to climate

change and environmental protection, Luntz advised the Republican administration on

the language that should be emphasized. For example, policy communicators need to

emphasize sound science as the guide for policy decisions, that risk must be identified

prior to decision-making and that technology and innovation will lead the preservation

of the environment.

Policy decisions must be presented as common sense solutions. “The facts are

beside the point. Facts only become relevant when the public is receptive and willing

to listen to them” (Luntz, Straight Talk). Other political communication consultants

share the same conviction that language and ordering of arguments will affect how an

audience receives the message. “It is not enough to present evidence; you have to

change the frame” (Mooney, 2003).

How different types of audiences receive and perceive various messages is core

to the discipline of communication. Researchers and practitioners alike are interested

in the elements of successful persuasion. How and what an administration

communicates can affect and be affected by public opinion. Can policy

communications make or break issues through the use of frames? Will an

administration ultimately fail because it chose to focus on facts rather on the frame?

And what about the public, do they not want the simple truth? Is truth not the mere

presentation of “facts”?

1

The Concept of Framing

Research on framing has increased dramatically over the last twenty years.

Scheufele (1999) categorized previous framing research along two dimensions: the

type of frame (media frame versus audience frame) and operationalization (as an

independent or dependent variable). This two-by-two typology demonstrates the broad

range and versatility of framing concepts and clarifies previous attempts to study

framing effects. But perhaps most revealing through this analysis is that framing

should be viewed through a process model. In Scheufele’s analysis (1999), the model

includes frame building, frame setting, individual level processes of framing, and

feedback loop from audiences to journalists. The implication here is that framing takes

on a different definition depending on context, or place in the process of

communication. Media and audience frames are conceptualized as distinct variables,

where media frames refer to the formulation of content in the message and audience

frames refer to how individuals remember the issues they learn from the media.

The concept of framing should be defined under the social constructivist

paradigm (Scheufele, 1999). Based on the main assumption that realities or “facts” are

constructed through human interaction, framing becomes one of the central ways

through which communicators may influence perceptions and understanding of a given

situation. Under these views, the path of framing influence extends from the

communicator’s presentation of a set of information related to an issue to subsequent

problem formulation in the receiver’s mind. Framing theory then, hypothesizes that

realities or facts can be reconstructed through presentation.

Framing has been described in various ways. Both Iyengar and Popkin

conceptualized framing as shifting the point of view of the observer so as to alter the

explanation and formulation of a problem. This way of viewing framing effects is

2

3

based on the assumption is that problem definition leads to solution definition. This

cognitive mechanism is supported by evidence from earlier psychological experiments

on judgment and choice.

In Tversky and Kahneman’s (1982) classic decision-making study, respondents

were exposed the following problem and one of two versions of proposed solution

sets:

The Asian Disease

Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease,

which is expected to kill 600 people. Two alternative programs to combat the

disease have been proposed. Assume that the exact scientific estimates of the

consequences of the programs are as follows:

Version 1

If Program A is adopted, 200 people will be saved. If Program B is adopted,

there a one-third probability that 600 people will be saved and a two-thirds

probability that nobody will be saved. Which one of the programs would you

favor?

Version 2

If Program A is adopted, 400 people will die. If Program B is adopted, there a

one-third probability that nobody will die and a two-thirds probability that 600

people will die. Which one of the programs would you favor?

Even though the consequences between the two programs remained identical,

the majority of respondents exposed to Version 1 chose Program A whereas in

Version 2, the majority of respondents favored Program B (Tversky & Kahneman,

1982). The authors theorized that these results illustrated framing effects because

4

simple changes in language were enough to draw different choices. The single

manipulation was changing the words from “will be saved” to “will die”. Framing

effects, then, can be narrowly defined as “discrepancies between choice problems that

decision makers, upon reflection, consider effectively identical” (Kahneman, 2003).

More broadly, framing has been defined as the “central, organizing idea or

theme of a message” (Gamson and Modigliani, 1987, p. 3). Framing and reasoning

devices were identified as tools by which the media portrays events to the public.

They argued that media frames must maintain “narrative fidelity” to be effective in

giving meaning to an issue. This meant that the media should utilize issue frames that

resonate with other culturally or socially accepted narratives (5). However, the study

did not focus on how narratives connect with audiences or the cognitive mechanisms

that underlie interpretation and the construction of meaning from media discourse.

Content analysis supported Gamson and Modigliani’s assertions that media

frames contain subtle devices that can give meaning to an issue (Entman, 1991). U.S.

news coverage of the KAL and Iran plane crashes were coded for keywords,

metaphors, symbols, and size. Entman theorized that words themselves act as frames

which serve to place events into categories that may imply a moral or normative value.

Like Gamson and Modigliani, Entman (1991) concluded that framing should include

components that “cohere with an established discursive domain…that form a way of

reasoning about a matter that is familiar to audiences from other cultural experiences”

(11).

Entman’s research suggests that language contained in frames can tap

associations of ideas that combine to form ways of reasoning about events that occur in

the world. More concretely, Entman (1993) described framing as, “select[ing] some

aspects of a perceived reality and make them more salient in a communicating text in

5

such ways as to promote a particular problem definition, causal interpretation, moral

evaluation, and/or treatment recommendation” (52).

Iyengar (1987) hypothesized that causal beliefs are important to predicting

public opinion and found some evidence to support this claim. Causal beliefs were

conceptualized as the spontaneous identification of causes contributing to complex

national issues and explanations for their outcomes. News frames influence causal

beliefs by orienting viewers to understand and explain national events in a particular

way. However, while the study described how the media can influence beliefs about

causal relations for given issues, cognitive mechanisms were not specified.

Examining attributions further, Iyengar (1989) explored the relationship

between attributions of responsibility, opinions, and attitudes. He operationalized two

dimensions of issue responsibility and theorized that causal attributions focus on the

origins of the issue and treatment attributions focus on the alleviation of issue or

problem solution. Based on the assumption that individuals are indeed cognitive

misers, reduction of political issues into questions of responsibility was theorized to be

an efficient way by which citizens think about national issues. Treatment

responsibility then, leads individuals to attribute responsibility to specific groups or

individuals.

Using fictitious stories that only varied in the opening and closing paragraphs,

researchers used an open thought-listing procedure to assess framing effects and found

that participants thought about ideas, feelings, and implications that were well beyond

the information in the stimulus (Price, Tewksbury, and Powers, 1997). These results

were consistent across four separate conditions. Although the direction of the thoughts

was attributable to the message frame, the range and variety of thoughts suggested that

audiences have various schemata that contributed to multiple ways of reasoning and

6

this led to distinct point of views. The authors considered possible cognitive

mechanisms and concluded, “By deflecting consideration of other ideas and feelings,

frame-induced knowledge activation can significantly influence decision making by

altering the mix of considerations brought to mind. Together, the two results illustrate

a kind of hydraulic pattern, with thoughts of one kind, stimulated by the frame, driving

out other possible responses ” (3).

In sum, framing research has focused on a variety of factors, ranging from

framing devices to audience reasoning and evaluation. Issue frames are a tangible part

of the persuasion process. It is one component of the message that can be controlled

and manipulated by the communicator. Extant research suggests that frames can be

subtle and audience responses may be measured in different ways. This research has

generally measured public opinion in response to a framed stimulus.

However, implied in the description of the “receptive audience” is that there

exists a non-tangible, less predictable component on the receiving end of persuasive

communications. Theorists have invoked Aristotle’s quote, “It adds to an orator’s

influence if ‘his hearers should be in just the right frame of mind’” (Popkin, 1991, p.

81). Although little research has examined the exact cognitive mechanisms that

contribute to opinion formation after frame exposure, there is evidence to suggest that

audience schemata are important elements in these cognitive processes.

The Concept of Schemata

Like framing, the concept of schema relies on social constructivist assumptions.

In Gestalt psychology, schemata have referred to configurations of prior knowledge

regarding people and situations. More generally, psychologists have defined schemata

as “organized knowledge structures that embodies important relationships among other

concepts in memory” (Schank & Abelson, 1995, p. 5). Other psychologists have

defined schemata as “cognitive structure[s] that represents one’s general knowledge

about a given concept or stimulus domain” and that includes “both attributes of a

concept and the relationships among the attributes” (Fiske & Taylor, 1984, p. 13).

Schemata and schemas are used interchangeably in the literature. Schemas

emphasize the active construction of reality because they can act as “perceptual filters”

(Price, 1992, p. 53). This is one route by which schemas influence public opinion.

Without schemas, individuals should perceive identical traits from the physical

environment and simultaneously view a constant reality because there is nothing to

alter singular perceptions of reality. In other words, schemas play a preconscious and

automatic role in cognitive processes. The construction of reality is the result of the

interplay between individual, schematic contributions, and physical stimuli from the

outside world (Fiske & Taylor, 1991, p. 99).

Once activated, one way that schemas can influence the formation of public

opinion is by bringing forward sets of interrelated ideas and information (53). The

structure, scope, and depth of existing schema can then alter the impact and association

of new, incoming information. Wick and Drew (1991) found evidence that when

individuals received information consistent with pre-existing knowledge, they are more

likely to make inferences and also recall more facts from the stimulus, demonstrating

7

8

that schemata play an important role in audience extrapolation of information they

receive from the media.

From the sociological perspective, Goffman (1974) defined schemata as

“frameworks” of interpretations people use to recognize and respond to events. He

wrote, “Each primary framework allows its user to locate, perceive, identify, and label

a seemingly infinite number of concrete occurrences defined in its terms” (21). From

this perspective, schemata are assumed to be applied automatically and unconsciously,

affecting how individuals relate to or describe an event.

Distinguishing between natural and social frameworks, different types of schemata are

linked to individual’s constructions of causality (Goffman, 1974). Natural frameworks

identify “unguided events” whose course and sources are non-human. In other words,

result of nature and not human action. Social frameworks, on the other hand, involve

some form of agency. These schemata account for “guided doings”, which results

from intentional human action.

Shared in psychological and sociological conceptualizations of schemata are

three characteristics. Schemata are conceptualized as an associative network of

explanations and expectations about the world. Furthermore, schemata play an

unconscious and automatic role in cognitive processes and affect how people receive

information. Finally, different schemata may be used to make attributions related to

different types of events.

Media effects researchers have proposed two routes by which public opinion is

influenced in a world filled with media messages (Price & Tewksbury, 1997). The

first route describes the media’s influence on public perceptions of important issues or

events and the second route elaborates how the media can focus the public’s attention

on particular aspects, or attributes, of events and issues. In other words, the extent and

9

range of media focus can alter the available information and ideas audiences think

about when forming an opinion.

Research over the last several decades has demonstrated that these routes are

not unidirectional, that media effects occur within interrelated processes. Media

influence is mediated by audience preferences and previous exposure, either through

direct experience or the media. Price and Tewksbury (1997) suggest that individual

issue frames are constructed through and within these processes, including recurring

media exposure, personal experience, and interaction with others.

Similarly, schema theorists hypothesize that schemata are developed through

two possible routes, personal experience and story-sharing. Personal experience is the

direct route to schema development whereas story-sharing is the indirect, or secondary,

route (Wyer & Carlston, 1994). Most publics must experience political processes or

national issues indirectly, through the intermediary of various media (Noelle-

Neumann, 1999). Issue frames may be one part of audience schemata toward a given

issue. Media discourse serve as “sets of interpretative packets that give meaning to an

issue” (Gamson and Modigliani, 1987, p. 3). Taken together, unless an individual has

direct experience with an issue, two major sources of schema development include the

media and the traditional story-sharing source, an individual’s interpersonal network.

Political theorists have argued that the schema concept is vague and has not

been adequately distinguished from other concepts such as scripts, attitudes, cognitive

maps, and frames (for a review, see Kuklinski, Luskin, & Bolland, 1991). Others have

suggested that narratives, scenarios, and scripts face the same conceptual challenge

(Popkin, 1991, p. 75). Although that debate is an ongoing and will not be addressed in

this study, theorists agree that, under the assumptions of schema theory, people make

sense of the world through schemata and tend to view and remember things in

10

conformity with their schemata. For the purposes of this study, it is useful enough to

distinguish scripts as event schema, a type of schema that contains explicit

expectations of behavior in a particular event. Together, the schemata and scripts

demonstrate that (1) expectations exist for any given situation based on prior exposure,

whether that exposure is through personal experience or is mediated through media,

and (2) other types of schemata exist, possibly ones that have direct political

implications.

Framing and Schemata

Frames have the potential to influence only when there are multiple points of

views, of which none are dominant (Popkin, 1991). The first step in framing an issue

is setting the reference point from which to look at a problem. Then, frames must cue

schemata based of degrees of representativeness and availability. Representativeness

refers to a “goodness of fit assessment”, or how the new information fits and coheres

with old information or an accepted narrative. Availability depends on the recency and

frequency to which the media presents an issue. Finally, the audience must be active in

connecting the information in the frame with information in their schemata. Framing

becomes effective in creating meaning when there is resonance between story frames

(from the media) and individual scripts (attained through personal experience and

interaction).

The recurring theme in the research cited thus far is that there is a relationship

between media frames and audience schemata in determining framing effects.

Whereas the media can set the reference point, or point of view through the use of

framing devices, these devices must connect with audience schemata. Without a

connection to these knowledge structures, individuals would have a difficult time

making sense of incoming media information.

11

The Applicability Model of Framing Effects

The role of schemata in framing effects was most specifically addressed in

Price & Tewsbury (1997). Framing was defined as an applicability effect and its

influence was conceptualized as a short-term cognitive process. In this model, media

frame must contain some information that is related to an individual’s knowledge store

in his or her schema. “The greater is the overlap between the features of some stored

knowledge and the attended features of a stimulus, the greater is the applicability of the

knowledge to the stimulus and the greater is the likelihood that the knowledge will be

activated in the presence of the stimulus” (Price & Tewksbury cited Higgins, 1996,

p. 135). Applicability, then, refers to the level of consonance between features in

individual schemata and features that are highlighted in the media frame.

Researchers have argued that framing is related to “the media’s ability to alter

the applicability of knowledge” and emphasized that “the exact psychological means

by which [framing] operates” is vague and is not supported by empirical evidence

(Price & Tewksbury, 1997, p. 176). They argue that the concept of schemata can be

used to account for how people process information. In the applicability model,

framing is a process by which the media activates some ideas while leaving out others.

Price and Tewksbury (1997) theorized, “Determination of fit between the

stored constructs and the environment occurs at the intersection of existing knowledge

and attributes of the stimulus situation noted by the perceiver” (190). In other words,

there is an automatic and unconscious “matching judgment” that is made between the

features of the message and relevant constructs in the receiver’s schemata. This

“matching” process partially explains why particular explanations and expectations are

activated over other information in an individual’s knowledge store.

12

13

Communicators can manipulate the salience of particular message attributes to

provoke an audience to attend to the message. For example, novelty is one way to

attract attention and increase the salience of an argument. Once applicable knowledge

is activated, individuals are hypothesized to be within a “train of thought” which then

determines the range of conclusions they can reach.

There are two assumptions in Price and Tewksbury’s model. First, the model

assumes that people have schemata or associative networks through which information

is interpreted and processed. Various constructs are linked together in this associative

network of explanations and expectations about the world, but these schematic links do

not form a predetermined hierarchy. In fact, the links may be “tangled” because

constructs can hold different and multiple positions in different sub-networks within

the larger schema network. Second, only small parts of schematic networks can be

activated and matched at any given time. The implication is that certain links in the

schema can be emphasized over other relationships in a given situation but these links

can change in light of new information or stimulus, highlighting other parts of the

schemata. The lack of hierarchy within the schematic structure accounts for

unpredictability in audience responses.

In short, the applicability model is a two phase approach to framing effects.

First, communication frames must resonate with underlying audience schemata in

order for pre-existing knowledge to be activated. Once an active train of thought is

engaged, framing effects occur when the attended features of the message corresponds

with the active constructs and relevant links in individual schemata.

This expectation stems from previous research on schemata. Psychologists

have found that people classify and recall schema consistent information more easily.

However, the relationship between schematic memory and schematic strength must

14

take into account knowledge and expertise in the given area. In other words,

knowledge and expertise contributes to the development of individual schemata.

Before information can be remembered, an individual must have available schemata

from which connections are made. Thus, individuals with underdeveloped schemata in

a particular topic area may be more susceptible to inconsistent information because

baseline information is unavailable (Fiske & Taylor, 1991).

This general hypothesis in schema theory has found support in studies relating

political issues. Political knowledge predicts expertise and expertise predicts

information recall that reflects a schema-consistent bias (Fiske, Lau, & Smith, 1990;

Lodge & Hamill, 1986). Furthermore, individuals with more developed political

schemata are more organized and extreme in their evaluations of the President,

political issues, and political candidates (Lusk & Judd, 1988; McGraw & Pinney,

1990).

Price & Tewksbury does not explicitly include a mechanism for true opinion

change as an outcome of framing effects. However, frequent and cumulative exposure

to non-applicable information regarding personally relevant issues combined with

conditions of uncertainty may motivate individuals to develop new or expand old

schemata. They write, “When particular constructs become subject to routine

activation and use over time, via applicability and accessibility, then there is certainly

the potential for long-term and perhaps cumulative effects” (199). The extent to which

chronic accessibility can influence schema development and change opinion is unclear

and not addressed in the current literature. Future studies might address schema and

opinion change over time but the current study is cross sectional in nature and will not

evaluate this issue.

The Current Study

Previous framing research has been summarized along two dimensions: the

type of frame, media frames versus audience frames, and operationalization, frames as

the independent versus dependent variable (Scheufele, 1999). Under this typology, the

current study is focused on the individual-level processes of framing. The study is

concerned with how audiences make attributions and evaluations upon exposure to a

framed message. Thus, there are two main independent variables in the study, the

framed message and relevant schemata. The dependent variables are causal

explanations, attributions of responsibility, and policy opinion.

Theoretical Expectations

The literature suggests several hypotheses. Based on the applicability model,

relevant schemata play the determining role in framing effects. The first set of

hypotheses center on factors contributing to schematic development, which is

operationalized as schema strength.

H1a: Attention to science and technology news content on television is

positively correlated with schema strength.

H1b: Attention to science and technology content in newspapers is positively

correlated with schema strength.

H1c: Seeking science and technology news content on the Internet is

positively correlated with schema strength.

The second set of hypotheses rely on schemata measures as the independent

variable. Based on schema theory, differences in schematic strength influence recall

and judgment of incoming information.

15

16

H2: Individuals with well developed schemata will recognize schema

consistent and inconsistent information better than individuals with

underdeveloped schemata. This will affect subsequent evaluations.

Previous findings suggest that framed messages can orient audiences to

particular causal attributions that are linked to attributions of responsibility.

Subsequent policy opinions are formed on the basis of these attributions. According to

schema theory and the applicability model, causal and responsibility attributions reflect

an individual’s schemata in relation to the information contained in frames.

H3a: Respondents with high schema strength will have schema consistent

attributions.

H3b: Respondents with low schema strength will have frame consistent

attributions.

H4a: Respondents with high schema strength will have schema consistent

policy opinions.

H4b: Respondents with low schema strength will have frame consistent

policy opinions.

The applicability model predicts that a “matching judgment” between salient

attributes of relevant schemata and of the frame must occur before there can be

framing effects. Therefore, for individuals with well developed schemata, effects will

be magnified when the frame resonates with the relevant schema. In other words,

respondents will identify strongly with frame and this will lead to more extreme

attributions and policy opinions.

H5a: When exposed to a resonating stimulus frame, respondents with

corresponding medium or high schema strength will have more extreme

causal attributions.

17

H5b: When exposed to a resonating stimulus frame, respondents with


attributions of responsibility.

H5c: When exposed to a resonating stimulus frame, respondents with


policy opinions.

Lastly, the order of schema measures may contribute to the effect of the frame.

Rotating the order of the frame stimulus and the order by which schema measures are

probed is a secondary manipulation in this study. Public opinion survey questions

often require respondents to specify and quantify an attitude. Researchers have pointed

to evidence that survey respondents often answer questions based on ideas and feelings

that are “top-of-mind” (Zaller & Feldman, 1992).

Consistent with the applicability model, this view assumes individuals have a

multitude of ideas and considerations in their mind. The top-of-mind view

hypothesizes that audiences will use a sample of ideas to answer questions and that this

sample of ideas may be based on a number of factors such as the survey itself, the

context of the question, and other recent events that may have triggered those ideas.

“Their choices do not, in most cases, reflect anything that can be described as true

attitudes; rather, they reflect the thoughts that are most accessible in memory at the

moment of response” (Zaller & Feldman, 1992, p. 580).

The design of the study is intended to find changes in attributions of cause and

responsibility and policy opinions that can be attributed to the frame stimulus.

However, given that previous theorizing has found that effects may sometimes be a

methodological artifact rather that real communication effects (Moy, Scheufele,

18

Eveland, & McCleod, 2001), the order in which schemas are measured will be

randomly rotated with the frame stimulus in order to provide two separate conditions,

one where respondents are asked the schema measures prior to frame exposure and the

other where respondents are asked the schema measures after the frame exposure.

Under the assumptions of the applicability model, it is expected that individual

schemata should remain independent of the frame stimulus. However, in a survey

design, the mere posing of the question may direct the respondents’ responses in subtle

ways and serve as a prime for other schemata. Thus, the following research question is

of interest:

RQ: In an experimental survey design, what are the potential effects of

measuring schemas in varying order?

Method and Design

Research on media frames and schemata has generally relied on experimental

methods. Experiments allow for elaborate manipulations of framing such as inclusion of

visual aids, highlighted print formats, and increased text. Open thought listing protocols

in experiments provide additional qualitative and quantitative measures that are better at

assessing the scope and content of audience schemata. The survey technique would have

difficulty emulating these qualities. However, while experiments can better address the

challenges of measuring schemas, smaller sample sizes and reliance on college student

samples can result in lower external validity and generalizability.

Using a computer-assisted telephone survey offers the benefit of large, national

samples. However, there are limitations of time and space on stimulus construction and

schema measures in the questionnaire. Closed-ended questions also restrict responses to

a predefined set of possible schemata representations. However, if results demonstrate

similar effects to those seen in experimental studies, the results would provide additional

support for previous theorizing.

Sampling

The sampling was drawn from a national representative household list and

respondents were selected by requesting either the male or female in the household with

the most recent birthday (N=781). The interviewing period began on October 26 and

ended on November 17, 2003. Interviews were conducted by students from a survey

research methods class and calls were made during evenings and weekends. The

response rate for this study was 55%, which counts both complete and partial interviews

as respondents in relation to the total number of households sampled, including non-

contacts and refusals.

19

20

The Issue: Biotechnology and Genetically Modified Foods

According to a recent Gallup poll and a survey sponsored by the Pew Initiative,

public awareness of issues related to biotechnology and genetically modified foods are

generally low in the U.S. Awareness is low even though genetically modified food

products have been in the market for almost ten years. This topic is appropriate as it

will present an issue where the public will have wide ranging awareness and schema

development.

Furthermore, under the definition of framing effects as “formulation effects”, in

order for framing effects to occur, there must not be a dominant point of view (Popkin,

1991). The labeling of genetically modified foods is a controversial issue over which

the public is divided. Proponents of labeling argue that consumers have the right to

information and to choose what foods to consume. They also argue that consumers

must be protected from the potential risks of genetically modified foods (GMFs).

Opponents of labeling have argued that it is in the interest of the state to promote

innovation in food production and there must be beneficial production arrangements

with the food industry in order for market GMFs. Overregulation may increase pricing

and decrease demand for innovation food products. These countering views provide

areas where schema development may be tested.

Frame Construction

In Straight Talk , Frank Luntz specified nine principles for Republican policy

communications on the environment and global warming. While the principles were

for speech and press release communications, space and time restrictions in the current

study required the creation of a brief message. Furthermore, previous research

provides evidence that mere changes in language were enough to elicit framing effects.

21

Thus, a few of Luntz’s principles were chosen based on relevancy and applicability to

biotechnology and were translated into frames that were a few sentences long. These

principles are listed in the Appendix.

Two frames were constructed, “Non-Regulation” and “Regulation”. The Non-

regulation frame (n=380 or 49%) emphasized scientific research before regulations are

implemented whereas the Regulation frame (n=401 or 51%) emphasized immediate

regulation and protection. Survey interviewers emphasized the underlined words when

reading the stimulus to each respondent.

Non-Regulation Frame

With genetically modified foods, we must not rush to judgment without all the

facts . And as a country, we need to invest in more research and development to

protect the future of our citizens. New regulations should only be made based

on good scientific information .

Regulation Frame

With genetically modified foods, we must identify all risks and health issues.

The FDA must protect our citizens by requiring research that ensures these

products are safe for humans and the environment. New regulations now will

protect our citizens from any future harm.

Schema Measures

Six ten-point scale items assessed the extent to which respondents agreed that

scientific information versus federal regulation should lead the treatment of

biotechnology issues. Items were grouped into “Information” versus “Regulation”

schemata and are listed in the appendix. Reliability coefficients for the Information

and Regulation schema measures were .44 and .63, respectively.

22

Two schema strength indicators reflected sum values of extremity scores for

Information and Regulation. Extremity scores were calculated by folding over the

original scale items into a five-point scale (“1”= zero schema strength to “5”=very high

schema strength). For example, a one or ten on the original agreement scale items

would indicate an extremity score of five. A total high extremity score of fifteen was

possible for each schema strength indicator. Relative to sample distribution,

respondents were then grouped into low, medium, and high schema strength groups

based on their total extremity scores.

Two other schema indicators were created to account for the direction of the

schema. These indicators of schema direction, “Information” and “Regulation”, were

additive indices of three ten-point scale items each; each schema direction indicator

could have a possible high score of thirty, indicating complete agreement with the

Information or Regulation statement. Respondents were again grouped into low,

medium, and high groups based on relative distribution. Each group contained

approximately 33% of respondents.

Antecedent Measures

Three separate measures assessed attention to science and technology news in the

media, including newspaper, television, and the World Wide Web. Two additional

measures assessed awareness of and support for biotechnology issues. All measures

used ten-point scales. Exact wording, means, and standard deviations for these measures

are reported in Table 1.

Demographic measures included gender (55 percent females), age (M=50.08,

SD=17.16), and education or years of formal schooling (M=14.63, SD=2.95). A measure

of ideology (M=8.34, SD=2.76) was also included; ideology was operationalized by

combining two seven-point scales of economic and social ideology (“1” = very liberal to

23

Table 1 Means and standard deviations for three measures:

attention to science and technology news across three media, awareness, and support

of biotechnologyA n t e c e d e n t M e a s u r e s M e a n S t a n d a r dD e v i a t i o nN e w s p a p e rW h e n y o u c o m e a c r o s s t h e f o l l o w i n g t y p e s o f s t on e w s p a p e r , h o w m u c h a t t e n t i o n d o y o u p a y t o t h( N e w s a b o u t s c i e n c e o r t e c h n o l o g y ) 5 . 6 9 2 . 7 0( " 1 " = l i t t l e a t t e n t i o n t o " 1 0 " = v e r y c l o s e a t t e n t i o n )T e l e v i s i o nW h e n y o u c o m e a c r o s s t h e f o l l o w i n g t y p e s o f c o nT V , h o w m u c h a t t e n t i o n d o y o u p a y t o t h e m ? ( N es c i e n c e o r t e c h n o l o g y ) 5 . 6 5 2 . 7 4( " 1 " = l i t t l e a t t e n t i o n t o " 1 0 " = v e r y c l o s e a t t e n t i o n )W o r l d W i d e W e bH o w o f t e n d o y o u g o o n l i n e f o r e a c h o f t h e f o l l o wp u r p o s e s ? ( T o s e e k o u t i n f o r m a t i o n a b o u t s c i e n ct e c h n o l o g y n e w s ) 3 . 9 9 3 . 0 2( " 1 " = l i t t l e a t t e n t i o n t o " 1 0 " = v e r y c l o s e a t t e n t i o n )A w a r e n e s s o f B i o t e c h n o l o g yA s y o u k n o w , s o m e f o o d p r o d u c t s a n d m e d i c i n e sd e v e l o p e d w i t h t h e h e l p o f n e w s c i e n t i f i c t e c h n i qg e n e r a l a r e a i s c a l l e d b i o t e c h n o l o g y a n d i n c l u d e ss u c h a s g e n e t i c e n g i n e e r i n g o r g e n e t i c a l l y m o d i f i eO n a s c a l e o f o n e t o t e n , w i t h o n e b e i n g N O T A Ta n d t e n b e i n g A G R E A T D E A L , w o u l d y o u t e l l m e hm u c h y o u h a v e h e a r d o r r e a d a b o u t t h i s i s s u e ?5 . 1 8 2 . 6 9

S u p p o r t o f B i o t e c h n o l o g yO v e r a l l , w o u l d y o u s a y y o u o p p o s e o r s u p p o r t t h eb i o t e c h n o l o g y i n a g r i c u l t u r e a n d f o o d p r o d u c t i o n ?u s e a t e n p o i n t s c a l e a g a i n w h e r e o n e m e a n s S T RO P P O S E a n d t e n m e a n s S T R O N G L Y S U P P O R T . 5 . 6 2 2 . 7 9

24

“7” = very conservative) into an additive index (r=.547, a=.000). Other items in the

survey were unrelated to the current study.

Procedure

All respondents were questioned on their level of attention to science and

technology news in the media, awareness of, and support for biotechnology prior to the

main manipulation. Respondents were randomly assigned to one of four conditions in a

two by two (frame x schema measure order) design. Half of the sample was exposed to

schema measures before the stimulus (“Schema First”) and the other half was exposed to

the stimulus before the schema measures (“Frame First”). The purpose of the random

ordering of the schema measures and the stimulus was to detect any differences due to

priming and control for accessibility effects. Respondents were also randomly split into

either the Non-regulation or the Regulation frame. Table 2 illustrates the double split

ballot design.

Table 2 Two by two experimental design

Regulation FrameSchema First

Regulation FrameSchema Second

Non-Regulation FrameSchema First

Non-Regulation FrameSchema Second

Type ofFrame

Order of Exposure to Schema Measures *

* Schema measures are identical across all four conditions

25

Immediately after exposure to the stimulus, all respondents were asked a

single-item manipulation check. The two frames, according to Tversky and

Kahneman’s narrow definition, should have identical content and differ only in the

point of view or reference point in the presentation. Since the messages should have

non-differentiated content, individuals should not be able to differentiate between or

consistently identify one group as the source of the message. However, based on H2,

differences are expected for respondents with highly developed schemata because they

are more likely to recognize schema-consistent and inconsistent information.

After the manipulation check, all respondents were exposed to three sets of

dependent measures, including causal attributions, attributions of responsibility, and

policy opinion. Respondents were not exposed to the causal attribution questions if

they did not feel biotechnology was risky. Demographic information was requested at

the end of the survey.

Dependent Measures

Four ten-point measures on causal attributions were used to create two

indicators, “Treatment” and “Global” causal attributions. Treatment attributions

represented attribution of risk to micro-factors such as individuals or government

policies whereas Global attributions represented attribution of risk to macro-factors

such as science and the nature of information. Each indicator was calculated as the

average of two items; respondents who chose not to answer any one of the items were

excluded. Correlations between items in the Treatment and Global causal attribution

indicators were both significant, r=.472, a=.000 and r=.355, a=.000, respectively.

Four ten-point scale measures assessed attributions of responsibility to four

different groups. These items were kept as separate measures since federal agencies,

26

independent organizations, private corporations and industry trade groups, and

consumers represent distinct entities.

Four ten-point scale measures on policy opinion were grouped into two

indicators, “Non-regulatory” and “Regulatory”, to represent support for a particular

policy principle. Support for “Non-regulatory” policy indicated agreement with

scientific information as a priority whereas support for “Regulatory” indicated

agreement with control and labeling regulations.

Each indicator was the average of two items. Items correlated at r= .266,

a=.000, and r=.427, a=.000, for the Non-regulatory and Regulatory policy indicators,

respectively. Table 3 contains the means and standard deviations for all dependent

measures.

27

Table 3 Means and standard deviations for outcome variablesO u t c o m e M e a s u r e s M e a n S t a n d a r dD e v i a t i o nG l o b a l A t t r i b u t i o n s 7 . 1 3 1 . 9 4T r e a t m e n t A t t r i b u t i o n s 6 . 9 5 2 . 0 4A t t r i b u t i o n o f r e s p o n s i b i l i t y t o U . S . g o v e r n m e n t o r f e da g e n c y 7 . 8 3 2 . 3 4A t t r i b u t i o n o f r e s p o n s i b i l i t y t o i n d e p e n d e n t , o r n o n -g o v e r n m e n t a l o r g a n i z a t i o n s 6 . 1 5 2 . 6 8A t t r i b u t i o n o f r e s p o n s i b i l i t y t o p r i v a t e c o r p o r a t i o n s a nt r a d e g r o u p s 5 . 7 0 3 . 0 1A t t r i b u t i o n o f r e s p o n s i b i l i t y t o i n d i v i d u a l c o n s u m e r s 6 . 1 2 2 . 9 7O p i n i o n t o w a r d s r e g u l a t i o n p o l i c y 8 . 0 6 1 . 9 1O p i n i o n t o w a r d s n o n - r e g u l a t i o n p o l i c y 7 . 3 3 2 . 0 0

Analyses and Results

Factors Contributing To Schema Strength and Direction

The four indicators, Information schema strength (M=8.33, SD=3.79) and

direction (M=20.90, SD=5.11), and Regulation schema strength (M=8.39, SD=3.97)

and direction (M=20.80, SD=5.80), were correlated against all antecedent measures

and demographic variables in bivariate analysis. An alpha level of .05 was used for all

statistical tests.

Age, gender, education, and ideology were uncorrelated with neither

Information schema strength nor schema direction. Interestingly, these measures were

correlated with Regulation schema strength. Age was slightly correlated with

Regulation schema strength (r=.076, a=.039). Gender (r=-.107, a=.004), education

(r=.095, a=.012), and ideology (r=-.127, a=.000) were correlated only with Regulation

schema direction. These correlations suggest that older, female, more educated, and

liberal respondents have stronger regulatory constructs in their schemata.

Information schema strength and direction was positively related to all types of

media attention, providing support for the three hypotheses in H1. This set of

hypotheses proposed that attention to media (across types) is positively related to

schema development but did not differentiate between the content of the schema,

regulation versus information. Attention to science and technology news stories in

newspapers was positively related to Information schematic strength at r=.108, a=.006.

Seeking science and technology news online was positively correlated with

Information schematic strength at r=.110, a=.012. Information schema direction was

also positively correlated with newspaper attention (r=.145, a=.000), television

attention (r=.167, a=.000), and information seeking online (r=.170, a=.000). In

28

29

particular, attention to science and technology news on television was positively

related to both Information and Regulation schematic strength at r=.119, a=.001 and

r=.091, a=.012, respectively. These findings are consistent with previous literature on

portrayal of science in the media.

Awareness of biotechnology was positively correlated with Information schema

strength (r=.140, a=.000) and direction (r=.166, a=.000) but not correlated with the

two Regulation schema indicators. Support of biotechnology was uncorrelated with

neither Information nor Regulation schema strength. However, support of

biotechnology was positively correlated with Information schema direction (r=.255,

a=.000) and negatively correlated with Regulation schema direction (r=-.083, a=.030).

Table 4 outlines these findings.

Manipulation Check

To assess the difference between the two framed statements, all respondents

were asked if they thought the statement (stimulus frame) came from an interest group

for or against regulations of genetically modified foods (GMFs). Excluding

respondents who refused to answer or answered “Don’t Know”, 75% of respondents

believed the statement came from an interest group for regulation of GMFs. However,

there was a significant difference between framed conditions (t(690)=-4.74, a=.00),

indicating that respondents exposed to the Regulation frame were more likely to

perceive the statement as coming from an interest group for regulation. There was no

difference between respondents who were exposed to the “Schema First and the

“Schema Second” conditions.

Further analysis revealed that respondents with high Regulation schema

strength were more likely to correctly identify the Non-regulation frame than

30

Tab

le 4

Tab

le 4

31

respondents with medium Regulation schema strength (t(211)=-2.05, p=.04) and low

Regulation schema strength (t(205)=-3.02, p=.00). Thus, Regulation schematic

strength is directly related to having a different perception of frame source (interest

group for or against regulation) between the two conditions. These findings

demonstrate two things: (1) respondents across both conditions generally assumed a

pro-regulation interest group as the source for the framed statements, and (2) support

for H2, which proposed that individuals with developed schemata are more likely to

recognize schema consistent information, i.e., respondents with high Regulation

schema strength were more like to notice the argument in the Regulation frame.

It is important to note, however, that parallel results were not found for the high

Information strength group; these respondents were not more likely to correctly

identify the Regulation frame. This difference may be attributable to the way that

information and regulation schemata are linked in the respondents’ minds. For

example, a regulation perspective on biotechnology may be automatically associated

with ideas about scientific information and research. In other words, to regulate

genetically modified foods is to require more information through labeling and

research.

Differences between Conditions

An independent-samples t-test found no differences between the four

conditions, demonstrating the lack of a main effect. However, by controlling for

schema strength, multiple t-tests were conducted and found differences that would

indicate an interaction effect between different schemata combinations and the

stimulus. The following findings provide limited support for the applicability model of

framing effects.29

32

Interactions between schema strength and frame stimulus. To test the

hypotheses on the role of schemata in influencing framing effects, t-tests were

conducted to look for differences between the two framed conditions while holding

schematic group constant. Exposure to the Regulation versus Non-regulation frames

resulted in differences in causal attributions for respondents across different schematic

groups.

Two different schematic groups (respondents with low Regulation and medium

Information schemata and respondents with low Regulation and high Information

schemata) were more likely to attribute risks associated with biotechnology to global

causes such as the nature of science and information if they were exposed to the Non-

Regulation frame, which emphasized that “new regulations should only be made based

on good scientific information” ((t(51)=2.20, p=.03 and t(9)=5.75, p=.00, respectively).

These differences in Global attributions were not found across the seven other

schematic groups. Figure 1 illustrates the differences across conditions and Table 5 in

the Appendix contains mean scores across all schematic groups.

Similarly, significant differences were found in the Treatment attributions of

two schematic groups across framed conditions. Treatment attributions represent the

reverse of Global attributions. Treatment attributions attribute the cause of risk to

government policies and individuals. As expected, when exposed to the Regulation

frame, which argued that the FDA must require research and create regulations to

protect citizens from unsafe products, respondents with stronger schemata (medium

Regulation and high Information schematic strength) were more likely to agree with

treatment as the cause of risk (t(35)=-2.36, p=.02). However, in direct contrast,

respondents with low Regulation and medium Information schemas were less likely to

agree with Treatment attributions (t(51)=2.73, p=.01). Figure 2 illustrates the

33

Figure 1 Effect of frame on Global attributions for

respondents from two schematic groups

0 . 0 02 . 0 0

4 . 0 06 . 0 08 . 0 0

1 0 . 0 0

N o n - R e g u l a t i o n R e g u l a t i o nF r a m e

Gl ob alA tt rib uti ons

A v e r a g e S c h e m a S t r e n g t h L o w R e g a n d M e d I n f o L o w R e g a n d H i g h I n f o

34

Figure 2 Effect of frame on Treatment attributions for

respondents from two schematic groups

0 . 0 02 . 0 0

4 . 0 06 . 0 08 . 0 0

1 0 . 0 0

N o n - R e g u l a t i o n R e g u l a t i o nF r a m e

T reat mentA tt rib uti ons

A v e r a g e S c h e m a S t r e n g t h L o w R e g a n d M e d I n f o M e d R e g a n d H i g h I n f o

35

differences across conditions and Table 6 in the Appendix contains mean agreement

with Treatment attributions across all schematic groups.

Next, differences in attributions of responsibility to specific groups were only

significant in one particular schema group and only when the responsible group in

question was the government. Respondents with high Regulation and low Information

schema strength who were exposed to the Non-regulation frame were more likely to

attribute responsibility to the government (t(14)=2.67, p=.02). Figure 3 illustrates this

finding and Table 7 in the Appendix details results across other schematic groups.

Parallel differences were not found for the other three dependent measures

which asked respondents whether groups such as private corporations, non-

governmental organizations, and individuals are responsible for ensuring the safety of

genetically modified foods. Table 8 through 10 in the Appendix details these non-

significant findings. These findings provide partial support for the two hypotheses

(H3a and H3b), which stated that respondents with high schema strength were

expected to be immune to the frame stimulus whereas respondents with low schema

strength are more susceptible to framing effects. However, there is only partial support

because differences were found only in a particular schematic strength group and not in

others.

Together, H4a and H4b stated the expected differences in policy opinion

between schema groups upon exposure to the framed stimulus. No interactions

between schema strength and stimulus frame were found to elicit differences in policy

agreement. This set of hypotheses was not supported as respondents across all

schematic groups were not affected by the frame in their policy opinions. Tables 11

and 12 in the Appendix details these findings.

36

Figure 3 Effect of frame on attributions of responsibility to government for

respondents with high Regulation and low Information schema strength

0 . 0 02 . 0 0

4 . 0 06 . 0 0

8 . 0 01 0 . 0 0

N o n - R e g u l a t i o n R e g u l a t i o nF r a m eR esponsibili t yA tt rib uti on

t oG o vernment alA genci es

A v e r a g e S c h e m a S t r e n g t h L o w R e g a n d M e d I n f o

37

Interactions between schema strength, direction of schema, and frame. T-tests

between conditions were conducted while controlling for schema strength and

direction to test the fifth set of hypotheses. H5a, H5b, and H5c most directly addressed

the predictions of the applicability model. These hypotheses stated that increased

resonance between the frame and the underlying schema would result in more extreme

causal and responsibility attributions as well as policy opinion. However, no

significant interactions were found.

Interaction between frame, schema order, and schema strength. Multiple

three-way interaction effects were found between schema order and framed conditions

for particular schematic strength groups. Tables 13 to 28 in the Appendix details these

mixed findings. In line with theoretical expectations, schema order had a magnifying

effect for particular schematic groups across various measures of responsibility

attribution and policy opinions. However, some results were unexpected and can not

be attributed to the frame or the schema order.

Agreement with policy principles differed for two groups that were exposed the

schema measures after the frame. First, respondents with low Regulation and low

Information schema strength who were exposed to the Regulation frame and the

schema measures afterwards were less likely to agree with Information policy

principles (t(55)=-2.16, p=.04). Secondly, respondents with low Regulation and

medium Information schema strength who were exposed to the Non-regulation frame

and the schema measures afterwards were less likely to agree with the Regulatory

policy principles (t(33)=-2.30, p=.03). Together, these results suggest that the order of

schema measures makes a marked difference on policy opinion by further directing the

association of ideas in the respondent’s mind after exposure to the frame. Figure 4 and

38

5 illustrates these interactions. Tables 19 and 28 in the Appendix contain the results

for other schematic groups in these conditions.

Other results demonstrate the effect of the frame combined with the effect of

schema measures which followed. Respondents with medium Regulation schema

strength (with varying strengths of Information schema) who were exposed to the Non-

regulation frame and the schema measures second were more likely to attribute

responsibility to non-governmental organizations, private corporations and industry

trade groups, and consumers (see Appendix - Tables 16, 17, and 18, respectively).

Notably, in complete reversal, respondents with high regulatory schemata and

medium information schemata were less likely to attribute responsibility to non-

governmental agencies and private corporations (see Tables 16 and 18 in the

Appendix). This finding was somewhat paralleled in conditions where respondents

with medium Regulation and high Information schemata were exposed to the

Regulation frame and schema measures second (see Table 24). Here, respondents

attributed more responsibility to non-governmental agencies for ensuring the safety of

genetically modified foods.

A three way interaction between the Non-Regulation frame, schema order, and

schema strength was found for Treatment attributions (see Table 13). In line with

theoretical expectations, respondents with medium Regulation and medium

Information schemata were less likely to agree with treatment as the cause of risk in

biotechnology after exposure to the Non-Regulation frame. However, a second

finding, in Global attributions, was not consistent with theoretical expectations.

Respondents reported less agreement with global attributions, where higher agreement

with global attributions were expected for respondents who were exposed to the Non-

regulation frame and the schema measures second, particularly within schematic

39

Figure 4 Effect of schema order on agreement with Non-regulatory policy for

respondents with low Regulation and low Information schema strength

who were exposed to the Regulation frame

t(133) = -2.30, p=.03

4 5678

S c h e m a S e c o n d S c h e m a F i r s tC o n d i t i o n b y S c h e m a O r d e rA greewi th N on -regul at ory

P ol i cyP ri nci pl es

L o w R e g a n d L o w I n f o ( R e g u l a t i o n F r a m e )L o w R e g a n d L o w I n f o S c h e m a S t r e n g t hA v e r a g e S c h e m a S t r e n g t h

40

Figure 5 Effect of schema order on agreement with Regulatory policy for

respondents with low Regulation and medium Information schema strength

who were exposed to the Non-regulation frame

(t(55)=-2.16, p=.04)

A greement wi th R egul at ory

P ol i cyP ri nci pl es

41

groups of stronger Information schemas. Table 13 in the Appendix details this

unexpected finding.

Conclusions

The first set of results suggest that demographics are related to some content in

schemata, however, media attention are likely to be better predictors. Here,

demographics and media attention served as the independent variables and the schema

strength indicators served as dependent variables. Information schema strength was

undifferentiated between demographic groups whereas Regulation schema strength

varied between gender, age, educational, and ideological groups. In particular, older,

female, more educated and liberal respondents expressed stronger agreement with

regulatory schema measures.

Respondents who reported increased attention to science and technology across

all media also displayed higher Information schema strength and direction but not

Regulation strength and direction. In other words, media attention to science and

technology news is related to the belief that research and information is important to

guiding regulation. This suggests that through use of the media, the public learns

about and adopts a more positive view of scientific information and progress in

biotechnology. Survey data, however, can not assess the causal direction in this

relationship. The alternative explanation is that individuals with more positive

attitudes towards science and information consume media content in line with their

views.

Television was the only medium that was related to Regulation schema

strength, suggesting that television content on science and technology fuels competing

schemata. This finding is in line for previous research that television may cultivate

particular views of science, for example, that of a “mad scientist” or the potential

consequences of “man over nature”. Thus, respondents who obtain news from

42

43

television may also be heavy viewers who believe that regulations are necessary to

ensure safety.

Correlations between awareness of and support of biotechnology and schema

indicators further support the conclusion that increased awareness of biotechnology

and a positive attitude toward scientific processes is related to faith in an information

approach to public policy. Support of biotechnology appears to take into account both

types of schemata, Information and Regulation. Respondents who agreed more with

scientific information supported biotechnology whereas respondents who agreed more

with regulation of biotechnology were less supportive of biotechnology.

At first glance, the second set of findings, which were results from the

manipulation check, seemed to indicate that the frames were identifiably different in

content. Here, schema strength indicators became the independent variables and

source recognition was the dependent variable, representing correct recall of

information and evaluation of the statement. However, further analysis revealed that

the differences in perception were due to differences in schema strength. In

conformity with H2, the check served to confirm that the two frames were virtually

indistinguishable in content and demonstrated that individuals with stronger schemas

are more likely to recognize schema consistent information.

Unfortunately, the subtle differences between the two frames may have also

contributed to the weak findings for the next two sets of hypotheses. H3 and H4 were

based on the two independent variables, schema development and the stimulus frame.

Dependent variables for H3 and H4 were attributions and policy opinion, respectively.

As expected, low schema strength respondents who were more likely to be influenced

by the stimulus frames. However, this finding was robust only with causal attributions

44

and responsibility attribution to government but not with attributions of responsibility

to three other groups and policy opinions.

These findings suggest that when individuals possess regulatory schemata that

are weaker in nature, exposure to a regulation argument taps other available schemata.

The current study focused only on regulatory versus information schemata and found

stronger information schemata in respondents, especially those who utilized media for

science and technology news. In this study, the information schema seemed to

override the regulation argument presented. However, if the Regulation schema were

more developed, respondents were then more likely to assign the cause of risk to

individuals and government policies.

The findings on causal attributions were not completely in line with theoretical

expectations. The Regulation frame specified that “the FDA must protect American

citizens from dangers of genetically modified foods.” As expected, respondents

exposed to this message were more likely to disagree with Global attributions, which

attributed the cause of risk to general flaws in science and technology information.

However, respondents in the same group were also more likely to disagree with

Treatment attributions, which attributed the cause of risk to flaws in policy and

decisions in the treatment of the problem. One explanation for this may be that the

measures were unclear and unreliable. Language in the Regulation frame may have

triggered causal attributions that were different than those measures included in the

current design.

Another potential explanation for these results can be found in Zaller’s (1992)

Receive-Accept-Sample (RAS) model, which assumes that people will sample from

ideas already salient in their minds to form judgments. Thus, theory would predict that

45

schemas should naturally be consistent with subsequent attributions and policy

opinions. Another explanation may be that the schema measures themselves were

primes for subsequent evaluations and increased the salience of ideas in people’s

minds.

The findings from the frame, schema order and schema strength interactions

suggest that there is a process of knowledge activation that is similar to the “hydraulic

pattern” Price termed in 1997. This would imply that upon exposure to the frame,

respondents became more sensitive to the schema statements. Knowledge activation

via the frame suggests a priming effect (the respondents reported schema responses

based on salient ideas triggered by of the previous frame). In this sense, the schema

measures can no longer be independent measures of association of ideas and cognitive

structures in the respondents’ minds. Furthermore, in line with previous theorizing,

respondents report attitudes that are consistent with prior cognitive self-reports (Moy,

et al., 2002, 3).

Finally, there was no support for the three hypotheses included in H5. To test

one assumption of the applicability model, it was necessary to analyze the direction of

schema development (e.g. agree versus disagree) along with the frame. Resonance is

present if the direction of the respondent’s attitudes and of the argument expressed by

the frame is consonant. Here, attributions and policy opinions were, again, the main

dependent variables. Null findings suggest that the applicability model may not

accurately describe how framing effects occur. However, the results may be due to

instrument validity. By utilizing six closed-end measures in survey format, the design

may not have adequately captured audience schemata. Schemata are non-hierarchical

46

and multi-faceted and it is possible that the current survey design failed to probe in

depth, other pertinent schemata related to biotechnology issues.

Related, the manipulations introduced in this study were only a few sentences

long and were designed to be as identical as possible in content. It is possible that such

small differences were not enough to engage the audience to think and relate different

schemata to the issue at hand. Future designs should include more elaborate framing

techniques, or are longer in length, to provide a stronger message and points of schema

stimulation for audiences.

Discussion

The results from this study provided limited support for the applicability model

of framing effects. The stimulus frames did not result in any main effects across

conditions, which may be interpreted as support because main effects of the frame

were absent when schemata were unaccounted for. Another explanation for these

findings may be that the manipulation was not strong enough. This interpretation

would suggest that framing issues must include longer-term and more developed

messages, such as continued media coverage, televised speeches, and visual aids in

order to achieve effects.

The current findings suggest that in countries where development

communication strategies need to be formed around biotechnology issues, the role of

the audience and their underlying schemata takes on additional importance. Schematic

structures are multi-faceted with content that vary in both strength and direction.

Messages that may influence one segment of the audience may not influence others.

And when effects are measured in the aggregate, the individual group effects may not

be apparent.

The national survey sample used in this study necessitated the creation of a

brief message whereas previous studies on framing were experiments based on smaller

samples with greater control over the framed message as well as other factors such as

noise and environment. For example, a telephone interview can not control a

respondent’s focus or attention. Combined with factors such as other measures in the

survey, respondents may simply have chosen not to process the message. However,

one can also assume that noise effects were randomly distributed across the conditions.

47

48

The current data does strongly support the following: schema development is

directly related to different types of media consumption and schemata are directly

related to an individual’s causal attributions, attributions of responsibility, and policy

opinions towards issues surrounding regulation of biotechnology. Furthermore,

individual schema measures, causal and responsibility attributions, and policy

opinions, which included a total of 24 measures, were highly inter-correlated,

demonstrating the complexity of schematic structures. Taken together, the results

demonstrate the need, as Price and Tewksbury (1997) had pointed out, for continued

research into the specific cognitive mechanisms that underlying framing effects.

Furthermore, the interactions between schema strength and frame demonstrate

the importance of the role of schemata. The three-way interaction findings also

support this conclusion. In the present study, schematic structures seem to influence

framing effects by either acting as filters or as primes for subsequent thoughts.

Respondents’ schematic structures were significantly related to media use. This

finding suggests that campaigns for or against genetically modified foods must account

for media use in the audience.

Seemingly irrelevant schemata might also become relevant if frames were able

to tap them. This study did not focus on examining the milieu of schemata that are

applicable to issues related to biotechnology. Mixed findings across some of the

schematic groups suggest that unmeasured schemata may be influencing people’s

responses to the dependent measures.

One possible explanation for the mixed findings may be that there were

framing effects but the measures constructed for this survey were not able to capture

other relevant effects. Future studies might proceed to increase instrument validity and

49

control through experimentation in a lab environment, however, generalizability and

external validity may be the trade-off.

Theory suggests that when tapped, other schemata can act as counter-frames, or

filters to a framed message. For example, a regulation frame may utilize stories of

illnesses that result from unsafe foods. Alternatively, a non-regulation frame might use

a story of children in poverty that can now be fed due to advances in agriculture. Both

these frames can tap other schemas using the human interest angle. These types of

frames may be used in counterarguments. Additionally, frames may also tap other

schemas to first engage the audience in order to present the main arguments.

To date, no other study has tested the applicability model. Theory and

experience still support Price and Tewksbury’s conceptualization of the applicability

model. The applicability model points out individuals are engaged in an “active train

of thought” when the information contained in frames resonate with existing schemata.

The advantage of this model is that it explains how knowledge activation spreads to

affect evaluations. Future studies utilizing a national survey design should incorporate

ways of focusing the respondent’s attention on the information contained in the frame

and further explore the differences in framing effects in relation to differences in

schematic strength. Experimental research is also necessary to clarify on how

knowledge activation can contribute to or detract from framing effects. Research can

also refine schema measures over time.

More research on the cognitive mechanisms underlying framing effects is

important for communication researchers, development communication, and policy

communication specialists. The applicability model predicted that relevant schemata

50

must be available and applied before framing effects can occur. Understanding these

processes will illuminate how to achieve persuasive communications through framing

techniques and devices.

APPENDIX

Principles applied in frame construction (Unpublished Report, Straight Talk )

(1) Sound science must be our guide in choosing which problems to tackle and

how to approach them.

(2) We should identify the real risks to human safety before we decide how to

address a problem.

(3) Technology, innovation, and discovery should play a major role in preserving a

clean and healthy environment.

(4) The best solutions to environmental challenges are common sense solutions.

Schema Measures

Three Information schema measures asked respondents to indicate the extent to which

they agreed with the following statements:

(1) Sound science must out guide in choosing which foods are safe.

(2) We need more information on the real risks to human health and safety before

we introduce more regulations.

(3) Scientific tests can decide whether or not a food product is definitely safe.

Three Regulation schema measures asked respondents to indicate the extent to which

they agreed with the following statements:

(1) Federal regulations will play a major role in preserving a clean and healthy

environment.

(2) Federal regulations are absolutely necessary to protect American consumers.

(3) More regulations are necessary before any more genetically modified

organisms are allowed in the food system.

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52

Causal Attribution Measures

Causal attribution measures were posed only to respondents who agreed that there are

risks associated with genetically modified foods.

Global attribution reflected the average of respondent’s agreement with the following

two statements about what causes environmental and health risks associated with

GMOs:

(1) There is not enough scientific research to prove or disprove human risks.

(2) Genetically modified foods are part of a new technology that is still

developing.

Treatment attributions reflected the average of respondent’s agreement with:

(1) Federal regulations are lacking.

(2) Consumers do not have enough information.

Attribution of Responsibility Measures

Respondents were to indicate the extent to which each of the following groups should

be responsible for ensuring the safety of genetically modified foods and agricultural

products.

(“1” = least responsible to “10” = most responsible)

(1) U.S. government or federal agency

(2) Independent, or non-governmental organizations

(3) Private corporations and industry trade groups

(4) Individual consumers

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Policy Opinion Measures

The non-regulatory policy indicator included the following two items:

(1) More experts should be recruited to evaluate GMOs.

(2) The U.S. should continue to support investments in biotechnology research.

The regulatory policy indicator included the following two items:

(5) There should be more control over GMOs.

(6) All genetically modified goods must be labeled.

Manipulation Check

Do you think this message came from a group in favor or opposed to biotechnology

and genetically modified foods?

54

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 1 0 7 . 1 6 - 0 . 3 6 4 9 5 0 . 7 2l o w l o w 6 . 2 4 6 . 1 4 0 . 2 5 6 7 0 . 8 1l o w m e d 7 . 5 2 6 . 5 9 2 . 2 0 5 1 0 . 0 3l o w h i g h 8 . 5 8 5 . 2 0 5 . 7 5 9 0 . 0 0m e d l o w 6 . 8 1 7 . 0 5 - 0 . 5 6 4 4 0 . 5 8m e d m e d 7 . 1 3 7 . 1 6 - 0 . 1 0 1 0 3 0 . 9 2m e d h i g h 7 . 3 4 8 . 1 5 - 1 . 1 9 3 4 0 . 2 4h i g h l o w 7 . 6 0 6 . 8 8 0 . 7 8 7 0 . 4 6h i g h m e d 7 . 7 3 7 . 5 7 0 . 3 3 5 0 0 . 7 4h i g h h i g h 6 . 9 6 7 . 7 3 - 1 . 6 6 1 1 4 0 . 1 0* a ) l a c k o f i n f o r m a t i o n a n d b ) t h e n a t u r e o f s c i e n c e .

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 0 2 6 . 8 9 0 . 7 0 4 9 5 0 . 4 9l o w l o w 5 . 7 1 5 . 8 1 - 0 . 2 5 6 6 0 . 8 1l o w m e d 6 . 9 6 5 . 8 3 2 . 7 3 5 1 0 . 0 1l o w h i g h 5 . 7 5 6 . 7 0 - 0 . 8 1 9 0 . 4 4m e d l o w 6 . 6 5 6 . 2 0 0 . 9 5 4 4 0 . 3 5m e d m e d 7 . 0 4 6 . 8 0 0 . 6 1 1 0 0 0 . 5 4m e d h i g h 6 . 9 4 8 . 3 3 - 2 . 3 6 3 5 0 . 0 2h i g h l o w 7 . 7 0 6 . 6 0 0 . 8 0 7 0 . 4 5h i g h m e d 7 . 4 3 7 . 1 9 0 . 4 0 4 8 0 . 6 9h i g h h i g h 7 . 8 7 7 . 7 0 0 . 3 9 1 1 8 0 . 7 0* a ) i n d i v i d u a l s a n d b ) g o v e r n m e n t p o l i c i e s .

M e a n a g r e e m e n t w i t h T r e a t m e n t A t t r i b u t i o n * m e a s u r e s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

T a b l e 5 D i f f e r e n c e s b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p sM e a n a g r e e m e n t w i t h G l o b a l A t t r i b u t i o n * m e a s u r e s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

T a b l e 6 D i f f e r e n c e s b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p sS c h e m a T y p e C o n d i t i o n b y F r a m e

S ch emati cS t rengthC omb i nati ons

D e g r e e t o w h i c h r e s p o n d e n t s a g r e e r i s k s a s s o c i a t e d w i t h b i o t e c h n o l o g y a r e a t t

S c h e m a T y p e C o n d i t i o n b y F r a m e


D e g r e e t o w h i c h r e s p o n d e n t s a g r e e r i s k s a s s o c i a t e d w i t h b i o t e c h n o l o g y a r e a t t

55

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 8 5 7 . 8 2 0 . 2 1 7 2 0 0 . 8 3l o w l o w 6 . 9 1 7 . 2 5 - 0 . 8 7 1 0 2 0 . 3 9l o w m e d 7 . 3 4 7 . 2 1 0 . 3 2 7 1 0 . 7 5l o w h i g h 8 . 2 2 8 . 2 7 - 0 . 0 6 1 8 0 . 9 5m e d l o w 7 . 6 0 7 . 1 9 0 . 8 9 7 7 0 . 3 8m e d m e d 7 . 9 4 7 . 6 4 0 . 8 4 1 4 7 0 . 4 0m e d h i g h 8 . 5 8 8 . 8 7 - 0 . 4 9 5 2 0 . 6 2h i g h l o w 9 . 6 7 7 . 7 1 2 . 6 7 1 4 0 . 0 2h i g h m e d 7 . 8 2 7 . 8 3 - 0 . 0 1 7 2 0 . 9 9h i g h h i g h 8 . 2 2 8 . 5 4 - 0 . 7 2 1 5 1 0 . 4 8*

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 2 0 6 . 1 2 0 . 3 9 7 0 9 0 . 7 0l o w l o w 5 . 5 1 5 . 9 8 - 1 . 0 0 1 0 0 0 . 3 2l o w m e d 5 . 9 1 5 . 3 2 1 . 1 9 7 1 0 . 2 4l o w h i g h 5 . 5 6 6 . 5 0 - 0 . 8 8 1 7 0 . 3 9m e d l o w 6 . 4 4 5 . 6 7 1 . 6 0 7 7 0 . 1 1m e d m e d 6 . 1 7 6 . 4 8 - 0 . 7 7 1 4 2 0 . 4 4m e d h i g h 5 . 7 8 6 . 4 5 - 0 . 7 6 5 2 0 . 4 5h i g h l o w 6 . 3 8 5 . 2 9 0 . 7 5 1 3 0 . 4 7h i g h m e d 6 . 4 5 6 . 3 4 0 . 1 6 7 1 0 . 8 8h i g h h i g h 6 . 6 7 6 . 2 8 0 . 7 3 1 5 0 0 . 4 7*



D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p i s r e s p o n s i b l e f o r e n s u r i n g t h e s ag e n e t i c a l l y m o d i f i e d f o o d p r o d u c t s .

T a b l e 7 D i f f e r e n c e s b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p sM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o t h e U . S . g o v e r n m e n t a n d f e d e r a l( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

S c h e m a T y p e C o n d i t i o n b y F r a m eT a b l e 8 D i f f e r e n c e s b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p sM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o i n d e p e n d e n t , o r n o n - g o v e r n m e n t a l( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )


D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p s a r e r e s p o n s i b l e f o r e n s u r i n g t h eg e n e t i c a l l y m o d i f i e d f o o d p r o d u c t s .

56

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 1 0 6 . 1 5 - 0 . 2 5 7 1 4 0 . 8 0l o w l o w 5 . 7 0 5 . 9 5 - 0 . 5 1 1 0 0 0 . 6 1l o w m e d 6 . 0 0 5 . 6 6 0 . 6 0 6 9 0 . 5 5l o w h i g h 7 . 3 3 5 . 7 0 1 . 0 7 1 7 0 . 3 0m e d l o w 6 . 4 1 6 . 2 5 0 . 2 8 7 8 0 . 7 8m e d m e d 6 . 2 5 6 . 2 2 0 . 0 7 1 4 6 0 . 9 4m e d h i g h 6 . 3 9 6 . 1 0 0 . 3 4 5 2 0 . 7 4h i g h l o w 5 . 6 7 6 . 7 1 - 0 . 5 3 1 4 0 . 6 0h i g h m e d 6 . 1 8 6 . 1 5 0 . 0 4 7 1 0 . 9 7h i g h h i g h 5 . 8 1 6 . 4 7 - 1 . 1 5 1 5 1 0 . 2 5*

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 5 . 4 8 5 . 9 1 - 1 . 8 9 7 1 2 0 . 0 6l o w l o w 4 . 6 1 5 . 1 8 - 1 . 2 1 1 0 0 0 . 2 3l o w m e d 5 . 5 4 5 . 1 4 0 . 7 2 7 0 0 . 4 8l o w h i g h 5 . 6 7 6 . 8 9 - 0 . 7 0 1 6 0 . 4 9m e d l o w 5 . 6 1 5 . 9 2 - 0 . 5 2 7 8 0 . 6 1m e d m e d 5 . 7 6 5 . 8 4 - 0 . 1 8 1 4 5 0 . 8 6m e d h i g h 5 . 5 7 5 . 6 3 - 0 . 0 7 5 1 0 . 9 4h i g h l o w 4 . 5 6 6 . 4 3 - 1 . 1 2 1 4 0 . 2 8h i g h m e d 4 . 7 4 6 . 2 3 - 1 . 9 4 7 2 0 . 0 6h i g h h i g h 6 . 0 7 6 . 6 9 - 1 . 1 1 1 5 0 0 . 2 7*



D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p s a r e r e s p o n s i b l e f o r e n s u r i n g t h eg e n e t i c a l l y m o d i f i e d f o o d p r o d u c t s .

M e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o c o n s u m e r s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

T a b l e 1 0 D i f f e r e n c e b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p s



D e g r e e t o w h i c h r e s p o n d e n t s a g r e e c o n s u m e r s a r e r e s p o n s i b l e f o r e n s u r i n g t h eg e n e t i c a l l y m o d i f i e d f o o d p r o d u c t s .

M e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o p r i v a t e c o r p o r a t i o n s a n d i n d u s t r y( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

T a b l e 9 D i f f e r e n c e s b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p s

57

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 8 . 0 6 8 . 0 6 0 . 0 3 7 0 5 0 . 9 7l o w l o w 7 . 2 4 7 . 2 1 0 . 0 8 9 9 0 . 9 4l o w m e d 7 . 6 4 7 . 3 1 0 . 8 5 6 9 0 . 4 0l o w h i g h 7 . 5 0 7 . 7 3 - 0 . 2 4 1 7 0 . 8 2m e d l o w 7 . 4 9 7 . 6 0 - 0 . 2 8 7 4 0 . 7 8m e d m e d 8 . 1 8 7 . 9 1 0 . 8 9 1 4 3 0 . 3 8m e d h i g h 7 . 5 0 8 . 5 5 - 1 . 7 9 5 0 0 . 0 8h i g h l o w 7 . 8 3 9 . 3 8 - 1 . 3 9 1 5 0 . 1 8h i g h m e d 8 . 4 2 8 . 7 0 - 0 . 6 6 7 2 0 . 5 1h i g h h i g h 9 . 0 5 8 . 8 3 0 . 7 2 1 5 0 0 . 4 76 8 9*

R e g u l a t i o I n f o r m a t i o n N o n - R e g u l a t i o n R e g u l a t i o n t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 3 3 7 . 3 3 - 0 . 0 3 6 9 4 0 . 9 7l o w l o w 6 . 3 4 6 . 5 4 - 0 . 6 3 9 8 0 . 5 3l o w m e d 7 . 3 5 6 . 9 5 1 . 0 9 6 9 0 . 2 8l o w h i g h 7 . 2 2 8 . 1 4 - 1 . 3 6 1 8 0 . 1 9m e d l o w 6 . 5 4 7 . 1 5 - 1 . 5 1 7 1 0 . 1 4m e d m e d 7 . 3 8 7 . 1 8 0 . 6 4 1 4 0 0 . 5 2m e d h i g h 7 . 3 3 7 . 5 0 - 0 . 2 9 5 0 0 . 7 7h i g h l o w 7 . 0 0 7 . 0 7 - 0 . 0 6 1 3 0 . 9 6h i g h m e d 7 . 8 7 7 . 5 7 0 . 5 2 6 7 0 . 6 1h i g h h i g h 8 . 0 6 8 . 0 5 0 . 0 3 1 5 2 0 . 9 8*

M e a n a g r e e m e n t w i t h I n f o r m a t i o n P o l i c i e s *( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )T a b l e 1 1 D i f f e r e n c e b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p sM e a n a g r e e m e n t w i t h R e g u l a t i o n P o l i c i e s *

T a b l e 1 2 D i f f e r e n c e b e t w e e n f r a m e d c o n d i t i o n s b y s c h e m a g r o u p sS c h e m a T y p e C o n d i t i o n b y F r a m e


D e g r e e t o w h i c h r e s p o n d e n t s a g r e e w i t h p o l i c i e s t h a t e m p h a s i z e s c i e n t i f i c r e s e ai n f o r m a t i o n a s w a y t o a d d r e s s b i o t e c h n o l o g y i s s u e s .



D e g r e e t o w h i c h r e s p o n d e n t s a g r e e w i t h p o l i c i e s t h a t e m p h a s i z e r e g u l a t i o n a s ta d d r e s s b i o t e c h n o l o g y i s s u e s .

58

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 1 1 7 . 1 5 - 0 . 2 3 4 9 5 0 . 8 2l o w l o w 6 . 0 9 6 . 4 3 - 0 . 5 5 2 9 0 . 5 9l o w m e d 7 . 6 3 7 . 4 7 0 . 2 7 2 4 0 . 7 9l o w h i g h 7 . 8 3 9 . 3 3 - 3 . 1 8 4 0 . 0 3m e d l o w 6 . 8 7 6 . 7 3 0 . 2 9 2 4 0 . 7 8m e d m e d 6 . 9 4 7 . 5 0 - 1 . 0 7 4 8 0 . 2 9m e d h i g h 7 . 3 8 7 . 3 1 0 . 0 5 1 4 0 . 9 6h i g h l o w 9 . 0 0 6 . 6 7 3 . 0 1 3 0 . 0 6h i g h m e d 7 . 6 1 7 . 8 1 - 0 . 3 2 2 0 0 . 7 5h i g h h i g h 6 . 8 9 7 . 0 7 - 0 . 2 4 5 2 0 . 8 1* a ) l a c k o f i n f o r m a t i o n a n d b ) t h e n a t u r e o f s c i e n c e .

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 8 5 7 . 0 6 - 1 . 1 2 4 9 5 0 . 2 7l o w l o w 5 . 7 1 5 . 7 1 - 0 . 0 1 2 9 0 . 9 9l o w m e d 6 . 5 6 7 . 1 4 - 1 . 3 7 2 4 0 . 1 8l o w h i g h 5 . 8 3 5 . 6 7 0 . 1 1 4 0 . 9 2m e d l o w 6 . 6 1 6 . 7 1 - 0 . 1 8 2 4 0 . 8 6m e d m e d 6 . 5 5 7 . 9 4 - 2 . 4 8 4 9 0 . 0 2m e d h i g h 7 . 1 9 6 . 7 2 0 . 4 9 1 5 0 . 6 3h i g h l o w 8 . 2 5 7 . 3 3 0 . 6 4 3 0 . 5 7h i g h m e d 7 . 0 0 7 . 6 9 - 0 . 8 8 1 9 0 . 3 9h i g h h i g h 8 . 0 6 7 . 6 2 0 . 7 9 5 4 0 . 4 3* a ) i n d i v i d u a l s a n d b ) g o v e r n m e n t p o l i c i e s .

D e g r e e t o w h i c h r e s p o n d e n t s a g r e e r i s k s a s s o c i a t e d w i t h b i o t e c h n o l o g y a r e a t t r i b u t a b l e t o

M e a n a g r e e m e n t w i t h T r e a t m e n t A t t r i b u t i o n * m e a s u r e s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e r

S ch emati cS t rengthC ombi nati ons


T a b l e 1 3 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r eD i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m eM e a n a g r e e m e n t w i t h G l o b a l A t t r i b u t i o n * m e a s u r e s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )


T a b l e 1 4 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r eD i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m e

C o n d i t i o n b y S c h e m a O r d e rS c h e m a T y p e

59

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 8 8 7 . 7 8 0 . 6 0 7 2 0 0 . 5 5l o w l o w 6 . 5 5 7 . 2 2 - 1 . 0 8 4 1 0 . 2 9l o w m e d 7 . 5 0 7 . 2 6 0 . 4 2 3 3 0 . 6 8l o w h i g h 8 . 0 0 8 . 4 0 - 0 . 3 8 7 0 . 7 2m e d l o w 7 . 8 0 7 . 3 3 0 . 7 7 4 1 0 . 4 4m e d m e d 8 . 0 9 7 . 7 1 0 . 7 5 6 9 0 . 4 6m e d h i g h 8 . 7 3 8 . 4 6 0 . 3 6 2 2 0 . 7 2h i g h l o w 1 0 . 0 0 9 . 2 5 1 . 7 8 7 0 . 1 2h i g h m e d 7 . 9 5 7 . 6 8 0 . 2 9 3 7 0 . 7 7h i g h h i g h 8 . 2 5 8 . 1 8 0 . 1 0 7 2 0 . 9 2*

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 2 9 6 . 0 1 1 . 4 1 7 0 9 0 . 1 6l o w l o w 5 . 3 2 5 . 6 8 - 0 . 5 5 3 9 0 . 5 8l o w m e d 5 . 5 8 6 . 0 9 - 0 . 6 9 3 3 0 . 5 0l o w h i g h 5 . 7 5 5 . 4 0 0 . 3 1 7 0 . 7 7m e d l o w 6 . 7 2 6 . 0 6 0 . 9 8 4 1 0 . 3 3m e d m e d 5 . 8 4 6 . 7 3 - 1 . 6 3 6 7 0 . 1 1m e d h i g h 7 . 8 0 4 . 2 3 3 . 2 6 2 1 0 . 0 0h i g h l o w 5 . 5 0 7 . 2 5 - 0 . 7 3 6 0 . 5 0h i g h m e d 5 . 4 0 7 . 6 1 - 2 . 4 5 3 6 0 . 0 2h i g h h i g h 7 . 0 5 6 . 1 9 1 . 1 2 7 0 0 . 2 7*

M e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o t h e U . S . g o v e r n m e n t a n d f e d e r a l a g e n c i e( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e r


D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p i s r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e n e t i c ap r o d u c t s .D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m eM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o i n d e p e n d e n t , o r n o n - g o v e r n m e n t a l o r g a n i z a

D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m e

S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e r


D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p s a r e r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e n ef o o d p r o d u c t s .

T a b l e 1 5 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n

T a b l e 1 6 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

60

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 2 9 5 . 9 5 1 . 5 4 7 1 4 0 . 1 3l o w l o w 6 . 3 0 5 . 1 7 1 . 4 2 4 1 0 . 1 6l o w m e d 5 . 9 2 6 . 0 5 - 0 . 1 6 3 1 0 . 8 7l o w h i g h 7 . 7 5 7 . 0 0 0 . 3 7 7 0 . 7 2m e d l o w 7 . 1 2 5 . 3 9 2 . 2 6 4 2 0 . 0 3m e d m e d 6 . 7 0 5 . 5 7 1 . 8 4 6 9 0 . 0 7m e d h i g h 6 . 2 0 6 . 5 4 - 0 . 2 5 2 1 0 . 8 0h i g h l o w 3 . 6 0 8 . 2 5 - 2 . 0 5 7 0 . 0 8h i g h m e d 5 . 4 5 6 . 9 5 - 1 . 4 2 3 7 0 . 1 6h i g h h i g h 5 . 8 8 5 . 7 3 0 . 1 8 7 2 0 . 8 6*

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 5 . 8 2 5 . 5 9 1 . 0 3 7 1 2 0 . 3 0l o w l o w 4 . 5 8 4 . 6 4 - 0 . 0 9 3 9 0 . 9 3l o w m e d 5 . 5 8 5 . 5 2 0 . 0 8 3 3 0 . 9 4l o w h i g h 6 . 7 5 4 . 8 0 0 . 7 0 7 0 . 5 1m e d l o w 5 . 5 2 5 . 7 4 - 0 . 2 5 4 2 0 . 8 0m e d m e d 5 . 4 2 6 . 3 0 - 1 . 2 4 6 8 0 . 2 2m e d h i g h 7 . 1 0 4 . 3 8 2 . 0 8 2 1 0 . 0 5h i g h l o w 4 . 0 0 5 . 2 5 - 0 . 4 7 7 0 . 6 5h i g h m e d 3 . 4 0 6 . 1 6 - 2 . 7 3 3 7 0 . 0 1h i g h h i g h 6 . 2 6 5 . 8 5 0 . 4 9 7 0 0 . 6 3* D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p s a r e r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e nf o o d p r o d u c t s .

C o n d i t i o n b y S c h e m a O r d e r



M e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o p r i v a t e c o r p o r a t i o n s a n d i n d u s t r y t r a d e g( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e r

D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m eM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o c o n s u m e r s

D e g r e e t o w h i c h r e s p o n d e n t s a g r e e c o n s u m e r s a r e r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e nf o o d p r o d u c t s .D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m e

S c h e m a T y p e ( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )T a b l e 1 7 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e

T a b l e 1 8 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e

61

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 8 . 0 1 8 . 1 2 - 0 . 7 5 7 0 5 0 . 4 6l o w l o w 7 . 5 3 7 . 0 0 1 . 0 7 4 0 0 . 2 9l o w m e d 6 . 7 5 8 . 1 1 - 2 . 3 0 3 3 0 . 0 3l o w h i g h 8 . 0 0 7 . 0 0 0 . 5 9 6 0 . 5 8m e d l o w 7 . 7 5 7 . 1 4 1 . 0 0 4 0 0 . 3 2m e d m e d 8 . 3 2 7 . 9 6 0 . 8 9 6 6 0 . 3 8m e d h i g h 8 . 0 0 7 . 0 8 0 . 9 2 2 2 0 . 3 7h i g h l o w 7 . 0 0 8 . 8 8 - 1 . 0 2 7 0 . 3 4h i g h m e d 8 . 4 8 8 . 3 7 0 . 1 6 3 7 0 . 8 7h i g h h i g h 9 . 0 0 9 . 1 0 - 0 . 2 4 7 1 0 . 8 1*

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 2 7 7 . 3 9 - 0 . 7 9 6 9 4 0 . 4 3l o w l o w 6 . 3 0 6 . 3 7 - 0 . 1 4 4 1 0 . 8 9l o w m e d 7 . 0 5 7 . 5 0 - 0 . 8 9 3 2 0 . 3 8l o w h i g h 8 . 0 0 6 . 6 0 1 . 2 6 7 0 . 2 5m e d l o w 6 . 7 6 6 . 2 8 0 . 7 6 3 7 0 . 4 5m e d m e d 7 . 5 1 7 . 1 5 0 . 8 2 6 6 0 . 4 1m e d h i g h 7 . 0 5 7 . 5 8 - 0 . 7 2 2 2 0 . 4 8h i g h l o w 6 . 1 3 7 . 8 8 - 0 . 9 4 6 0 . 3 8h i g h m e d 8 . 3 3 7 . 3 8 1 . 2 6 3 3 0 . 2 2h i g h h i g h 8 . 0 9 8 . 0 3 0 . 1 1 7 2 0 . 9 2*S ch emati cS t rength

C ombi nati ons

D e g r e e t o w h i c h r e s p o n d e n t s a g r e e w i t h p o l i c i e s t h a t e m p h a s i z e r e g u l a t i o n a s t h e w a y t o a d di s s u e s .

D e g r e e t o w h i c h r e s p o n d e n t s a g r e e w i t h p o l i c i e s t h a t e m p h a s i z e s c i e n t i f i c r e s e a r c h a n d m o r ew a y t o a d d r e s s b i o t e c h n o l o g y i s s u e s .

C o n d i t i o n b y S c h e m a O r d e rS c h e m a T y p e ( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m eM e a n a g r e e m e n t w i t h R e g u l a t i o n P o l i c i e s *( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )



M e a n a g r e e m e n t w i t h I n f o r m a t i o n P o l i c i e s *

S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e rT a b l e 1 9 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e

T a b l e 2 0 I n t e r a c t i o n s b e t w e e n t h e N o n - R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e

62

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 1 1 7 . 1 5 - 0 . 2 3 4 9 5 0 . 8 2l o w l o w 6 . 2 2 6 . 0 3 0 . 3 5 3 6 0 . 7 3l o w m e d 6 . 0 6 6 . 8 2 - 1 . 0 4 2 5 0 . 3 1l o w h i g h 5 . 0 0 5 . 5 0 - 0 . 5 1 3 0 . 6 5m e d l o w 7 . 3 8 6 . 5 6 1 . 0 3 1 8 0 . 3 2m e d m e d 6 . 8 7 7 . 5 4 - 1 . 5 2 5 3 0 . 1 3m e d h i g h 8 . 5 0 7 . 7 2 1 . 0 3 1 8 0 . 3 2h i g h l o w 6 . 0 0 7 . 7 5 - 1 . 9 4 2 0 . 1 9h i g h m e d 8 . 0 7 7 . 0 7 1 . 4 3 2 8 0 . 1 6h i g h h i g h 8 . 0 5 7 . 4 0 1 . 0 9 6 0 0 . 2 8* a ) l a c k o f i n f o r m a t i o n a n d b ) t h e n a t u r e o f s c i e n c e .

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 8 5 7 . 0 6 - 1 . 1 2 4 9 5 0 . 2 7l o w l o w 5 . 8 6 5 . 7 3 0 . 2 2 3 5 0 . 8 3l o w m e d 5 . 1 3 6 . 1 3 - 1 . 3 0 2 5 0 . 2 1l o w h i g h 6 . 3 3 7 . 2 5 - 0 . 3 9 3 0 . 7 2m e d l o w 6 . 2 5 6 . 1 3 0 . 1 4 1 8 0 . 8 9m e d m e d 6 . 4 3 7 . 3 0 - 1 . 6 6 4 9 0 . 1 0m e d h i g h 8 . 1 4 8 . 5 6 - 0 . 5 6 1 8 0 . 5 9h i g h l o w 5 . 7 5 7 . 1 7 - 0 . 9 3 3 0 . 4 2h i g h m e d 7 . 2 9 7 . 1 0 0 . 2 2 2 7 0 . 8 3h i g h h i g h 7 . 8 9 7 . 5 2 0 . 6 1 6 2 0 . 5 4* a ) i n d i v i d u a l s a n d b ) g o v e r n m e n t p o l i c i e s .

T a b l e 2 1 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n g tM e a n a g r e e m e n t w i t h G l o b a l A t t r i b u t i o n * m e a s u r e s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )






T a b l e 2 2 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n g tM e a n a g r e e m e n t w i t h T r e a t m e n t A t t r i b u t i o n * m e a s u r e s( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e r



63

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 8 8 7 . 7 8 0 . 6 0 7 2 0 0 . 5 5l o w l o w 6 . 9 4 7 . 6 1 - 1 . 3 6 5 9 0 . 1 8l o w m e d 7 . 2 9 7 . 1 7 0 . 1 9 3 6 0 . 8 5l o w h i g h 8 . 3 8 8 . 0 0 0 . 2 5 9 0 . 8 1m e d l o w 7 . 2 1 7 . 1 8 0 . 0 5 3 4 0 . 9 6m e d m e d 7 . 8 6 7 . 3 9 0 . 9 0 7 6 0 . 3 7m e d h i g h 9 . 5 3 8 . 2 0 1 . 6 1 2 8 0 . 1 2h i g h l o w 6 . 6 7 8 . 5 0 - 1 . 2 1 5 0 . 2 8h i g h m e d 7 . 6 3 8 . 0 0 - 0 . 4 1 3 3 0 . 6 9h i g h h i g h 8 . 3 8 8 . 7 3 - 0 . 6 0 7 7 0 . 5 5*

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 2 9 6 . 0 1 1 . 4 1 7 0 9 0 . 1 6l o w l o w 6 . 1 2 5 . 8 2 0 . 4 7 5 9 0 . 6 4l o w m e d 5 . 4 3 5 . 2 5 0 . 2 4 3 6 0 . 8 2l o w h i g h 6 . 4 3 6 . 6 7 - 0 . 1 2 8 0 . 9 1m e d l o w 5 . 1 6 6 . 2 4 - 1 . 5 8 3 4 0 . 1 2m e d m e d 6 . 3 5 6 . 6 3 - 0 . 4 8 7 3 0 . 6 3m e d h i g h 7 . 7 3 5 . 2 5 2 . 2 7 2 9 0 . 0 3h i g h l o w 5 . 3 3 5 . 2 5 0 . 0 5 5 0 . 9 7h i g h m e d 6 . 9 4 5 . 8 4 1 . 1 7 3 3 0 . 2 5h i g h h i g h 6 . 7 9 5 . 6 8 1 . 4 8 7 8 0 . 1 4*

D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p i s r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e n e tp r o d u c t s .

D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m eM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o t h e U . S . g o v e r n m e n t a n d f e d e r a l a g e n c iT a b l e 2 3 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n g


D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p s a r e r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e nf o o d p r o d u c t s .

( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

S c h e m a T y p e C o n d i t i o n b y S c h e m a O r d e rM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o i n d e p e n d e n t , o r n o n - g o v e r n m e n t a l o r g a n i z



T a b l e 2 4 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n gD i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m e( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

64

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 6 . 2 9 5 . 9 5 1 . 5 4 7 1 4 0 . 1 3l o w l o w 6 . 1 8 5 . 6 5 0 . 8 6 5 7 0 . 3 9l o w m e d 5 . 4 3 5 . 7 9 - 0 . 4 2 3 6 0 . 6 8l o w h i g h 5 . 0 0 7 . 3 3 - 0 . 9 2 8 0 . 3 9m e d l o w 5 . 5 3 7 . 0 6 - 1 . 8 8 3 4 0 . 0 7m e d m e d 6 . 5 1 5 . 8 9 0 . 9 3 7 5 0 . 3 6m e d h i g h 6 . 7 3 5 . 5 0 1 . 0 6 2 9 0 . 3 0h i g h l o w 6 . 0 0 7 . 2 5 - 0 . 4 0 5 0 . 7 1h i g h m e d 6 . 5 3 5 . 8 4 0 . 6 0 3 2 0 . 5 5h i g h h i g h 6 . 9 8 5 . 8 9 1 . 3 6 7 7 0 . 1 8*

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 5 . 8 2 5 . 5 9 1 . 0 3 7 1 2 0 . 3 0l o w l o w 5 . 3 9 4 . 9 3 0 . 7 1 5 9 0 . 4 8l o w m e d 5 . 4 3 4 . 9 6 0 . 5 4 3 5 0 . 5 9l o w h i g h 7 . 4 3 5 . 0 0 0 . 9 1 7 0 . 3 9m e d l o w 5 . 6 8 6 . 1 8 - 0 . 6 2 3 4 0 . 5 4m e d m e d 5 . 9 0 5 . 7 8 0 . 1 8 7 5 0 . 8 6m e d h i g h 6 . 7 9 4 . 6 3 1 . 8 1 2 8 0 . 0 8h i g h l o w 4 . 3 3 8 . 0 0 - 2 . 6 3 5 0 . 0 5h i g h m e d 7 . 3 1 5 . 3 2 1 . 9 4 3 3 0 . 0 6h i g h h i g h 6 . 9 5 6 . 3 8 0 . 7 6 7 8 0 . 4 5*



D e g r e e t o w h i c h r e s p o n d e n t s a g r e e t h e g r o u p s a r e r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e nf o o d p r o d u c t s .

( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )




D e g r e e t o w h i c h r e s p o n d e n t s a g r e e c o n s u m e r s a r e r e s p o n s i b l e f o r e n s u r i n g t h e s a f e t y o f g e nf o o d p r o d u c t s .

M e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o c o n s u m e r sT a b l e 2 5 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n g

T a b l e 2 6 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n gM e a n a g r e e m e n t w i t h a t t r i b u t i n g r e s p o n s i b i l i t y t o p r i v a t e c o r p o r a t i o n s a n d i n d u s t r y t r a d e g( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )


65

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 8 . 0 1 8 . 1 2 - 0 . 7 5 7 0 5 0 . 4 6l o w l o w 6 . 8 9 7 . 5 9 - 1 . 6 9 5 7 0 . 1 0l o w m e d 6 . 8 1 7 . 5 9 - 1 . 4 5 3 4 0 . 1 6l o w h i g h 7 . 8 1 7 . 5 0 0 . 2 3 9 0 . 8 2m e d l o w 7 . 3 9 7 . 8 4 - 0 . 8 3 3 2 0 . 4 2m e d m e d 7 . 6 6 8 . 1 9 - 1 . 2 0 7 5 0 . 2 3m e d h i g h 8 . 6 8 8 . 4 3 0 . 3 6 2 6 0 . 7 2h i g h l o w 9 . 8 3 9 . 1 0 0 . 6 1 6 0 . 5 7h i g h m e d 8 . 5 0 8 . 8 5 - 0 . 6 5 3 3 0 . 5 2h i g h h i g h 8 . 7 5 8 . 9 2 - 0 . 3 9 7 7 0 . 7 0*

R e g u l a t i o n I n f o r m a t i o n S c h e m a S e c o n d S c h e m a F i r s t t - s t a t i s t i c d f p - v a l u ea l l a l l 7 . 2 7 7 . 3 9 - 0 . 7 9 6 9 4 0 . 4 3l o w l o w 6 . 1 2 7 . 0 2 - 2 . 1 6 5 5 0 . 0 4l o w m e d 6 . 7 7 7 . 0 4 - 0 . 4 6 3 5 0 . 6 5l o w h i g h 8 . 1 3 8 . 1 7 - 0 . 0 5 9 0 . 9 7m e d l o w 6 . 7 6 7 . 6 3 - 1 . 9 2 3 2 0 . 0 6m e d m e d 6 . 9 5 7 . 4 6 - 1 . 2 0 7 2 0 . 2 4m e d h i g h 7 . 6 2 7 . 4 0 0 . 2 5 2 6 0 . 8 1h i g h l o w 6 . 3 3 7 . 6 3 - 0 . 7 2 5 0 . 5 0h i g h m e d 7 . 0 0 8 . 0 3 - 1 . 1 9 3 2 0 . 2 4h i g h h i g h 8 . 0 8 8 . 0 1 0 . 1 4 7 8 0 . 8 9*



D e g r e e t o w h i c h r e s p o n d e n t s a g r e e w i t h p o l i c i e s t h a t e m p h a s i z e s c i e n t i f i c r e s e a r c h a n d m o r ew a y t o a d d r e s s b i o t e c h n o l o g y i s s u e s .

M e a n a g r e e m e n t w i t h I n f o r m a t i o n P o l i c i e s *( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )

( 1 = " n o t a t a l l " t o 1 0 = " c o m p l e t e l y a g r e e " )D i f f e r e n c e s b e t w e e n s c h e m a o r d e r c o n d i t i o n s b y s c h e m a g r o u p s , c o n t r o l l i n g f o r f r a m eM e a n a g r e e m e n t w i t h R e g u l a t i o n P o l i c i e s *




D e g r e e t o w h i c h r e s p o n d e n t s a g r e e w i t h p o l i c i e s t h a t e m p h a s i z e r e g u l a t i o n a s t h e w a y t o a db i o t e c h n o l o g y i s s u e s .

T a b l e 2 7 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n g

T a b l e 2 8 I n t e r a c t i o n s b e t w e e n t h e R e g u l a t i o n f r a m e , s c h e m a o r d e r , a n d s c h e m a s t r e n g

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