Predicting Consumer Intentions to Purchase Genetically Modified Food
Bibliographic record
Abstract
Environmentalist are sceptical towards the burgeoning interests of consumers in GM crops and the products are under careful observation of the scientific researchers and policymakers present all around the globe. The objective of the paper is to examine the Developing Nation consumers intention towards GM Food as a purchase choice. To elucidate the role played by determinant factors such as Environmentalism and Emotional Involvement followed by factors from TPB was used to determine the consumer intentions. The study has exploited the hypermarket trends of Indian city, Chandigarh, which is capital to states of Haryana and Punjab, by using a cross-sectional survey comprising of 744 number of consumers. Result shows that among the five determinant factors, Attitude, Environmentalism and Perceived Behavioral Control are the key determinants that play a substantial role in influencing consumers to purchase GM Food. The findings of the study will prove beneficial in augmenting the adoption of GM Food by increasing social desirability and meeting the food security demand of India.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".