Why Consumers Don't see the Benefits of Genetically Modified Foods, and what Marketers can do about It
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Evidence from four studies suggests that the moral opposition toward genetically modified (GM) foods impedes the perception of their benefits, and critically, marketers can circumvent this moral opposition by employing subtle cues to position these products as being “man-made.” Specifically, if consumers view the GM food as man-made, and if they understand why it was created, moral opposition to the product diminishes, and the GM food's perceived benefits increase, which subsequently increases purchase intentions for the product. This effect is replicated in the field (in both controlled and naturalistic settings), in a laboratory experiment, and with an online consumer panel. The results suggest that marketers can help consumers better consider all information when assessing the merits of GM foods by using packaging and promotion strategies to cue consumers to view the GM food for what it is (i.e., a man-made object created with intent). The findings have implications for the recent GM food labeling debate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it