Organics, trust, and credibility: a management and media research perspective
Bibliographic record
Abstract
Our purpose was to qualify the relations between trust, credibility, and the field of organics by way of creating a dialogue between two independent Organic Research, Development and Demonstration Programme "MultiTrust" subprojects.Both projects explore the explanatory value of trust and credibility for the success of organic labels in the fields of management research and media research.Our key objectives were to critically scrutinize the trust and credibility constructs applied in each of these two fields, to reflect on their explanatory value in the performance of organics from both a management and media perspective, and to set out an agenda for future interdisciplinary research.We conclude that relations between organic products, labels, and consumers are still poorly understood, that the belief in organic labels' direct impact on consumer choices in favor of organic food purchase cannot be supported, and that the explanatory value of trust for the success of organic production remains unproven.We propose for future research to investigate the relevance of credibility and trust for organics in multidisciplinary mixed-methods studies that focus on the emergence of trust, as well as on other social factors impacting the success of organic production.This would best be achieved through interdisciplinary work.
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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 | 0.033 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.005 | 0.041 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| 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".