DECONSTRUCTING PUBLIC PERCEPTIONS OF NOVEL FOOD TECHNOLOGIES: HUMAN VALUES AND INFORMATION COMMUNICATION STRATEGIES
Bibliographic record
Abstract
Based on insights of behavioural economics, this thesis aims to provide a more nuanced understanding on determinants of consumers’ acceptance of novel food technologies. In particular, this thesis explores how consumers’ attitudes and food choices related to innovative food technologies are affected by ‘inside’ individual factors, such as underlying human values (i.e., cultural worldviews and food-related values), and ‘outside’ environmental factors, such as the information framing (i.e., narrative communication). Each paper focuses on one particular factor that motivates disparate assessments of food technologies.\n\nEmpirical data on consumers’ food technology attitudes and food choice behaviours were collected from a nation-wide Internet survey administered to 1608 Canadian consumers in 2016. Half of the respondents participated in the Biotechnology version survey, and the other half of respondents completed the Nanotechnology version survey. Both versions of online survey incorporated a choice experiment, where respondents selected their most preferred sliced apple products from a set of hypothetical alternatives. Each paper focuses on particular research questions thus uses different sections of this extensive survey.\n\nPaper 1 explores information framing effects by comparing the effectiveness of using logical-scientific vs. narrative information to communicate about food biotechnology to consumers. A logical-scientific information condition about biotechnology was developed and written in a scientific style using the passive voice with generalized and impersonal language. In contrast, a narrative-style information condition about the technology was written in a more lively and vivid personal style. Respondents were randomly assigned to different information treatments. Results indicate that information about food biotechnology shown in different formats (logical-scientific vs. narrative) or being accessed by respondents in different manners (forced exposure or voluntary choice) can have differing impacts on perceptions and preferences. Compared with logical-scientific information, narratives and/or voluntary information access could help to reduce the opposition to biotechnology.\n\nPaper 2 investigates an alternative psychosocial factor, cultural worldview, which has been underestimated or omitted when examining consumer acceptance of food biotechnology. Individuals’ cultural worldviews were measured by a slightly modified version of cultural cognition scale. Results suggest that individuals holding hierarchical (vs. egalitarian) and communitarian (vs. individualistic) worldviews tend to hold more positive attitudes and be more accepting of agricultural biotechnology.\n\nPaper 3 suggests that intermediary food-related values and their relative importance to consumers have significant powers in explaining attitudes and choices about foods produced by means of nanotechnology. Consumers are heterogeneous in their food values, i.e., they place different importance on food value items such as naturalness, appearance, convenience, safety and novelty. Although Canadian consumers, on average, prefer not to use nanotechnology in sliced apple production, their preferences are heterogeneous. ‘Supporters’ of nanotechnology applied to agriculture and food production are those who consider ‘appearance’ is an important value to food purchase. By contrast, ‘opponents’ tend to emphasize the importance of ‘naturalness’ and ‘origin’.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".