How do consumers react to food products labelled as “antibioticfree”?
Bibliographic record
Abstract
This study aims to answer the research question: How do consumers react to\nfood products labelled as “antibiotic-free”?, by unraveling whether\nconsumers are positively influenced by an “antibiotic-free” label affixed on\nproducts. We here investigate if the presence of an “antibiotic-free” label\npositively influences the respondent’s purchase intentions, the product’s\nperceived quality and taste, as well as the respondent’s trust towards the\nproduct, the price he is willing to pay to acquire the product, and if this price\nis affected by the respondent’s knowledge about antibiotics. We here focus on\nfood products and more especially on meat, investigating the French market\nand French consumers, in a context of blurred legislations due to a\ncontroversial ratification of the CETA, and in a climate of sanitary crisis\ncaused by the outbreak of the Covid-19.\nBy presenting respondents, thanks to an online experiment, with three\ndifferent products bearing one, three and no “antibiotic-free” label at all, we\ncame to the conclusion that the presence of an “antibiotic-free” label\ngenerates higher purchase intentions and willingness to pay, positively\ninfluences the product’s perceived quality, and positively influences trust\ntowards the product. However, we could not state that the presence of an\n“antibiotic-free” label on a product positively influences the perceived taste\nrespondents report. In addition to that, we conclude that there is a positive\nsignificant correlation between the respondents’ level of knowledge about\nantibiotics and their willingness to pay for products that bear at least one\n“antibiotic-free” label.\nTherefore, creating an official “antibiotic-free” label could be beneficial for\nEuropean and French meat producers, since there is a potential market for\nit. However, in order to maximize the sales, it seems to be crucial to educate\nthe French public to deepen their knowledge about antibiotics. Customers\nwith a thorough knowledge of antibiotics would be able to fully understand\nthe advantages of such a label, providing an additional value for the product\nbearing it, compared to a product imported from Canada, which may even\npresent risks for customers’ health.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".