Why did China's cost‐reduction‐oriented policies in food safety governance fail? The collective action dilemma perspective
Bibliographic record
Abstract
Abstract Consumer participation plays an important role in improving food safety. Current research shows that reducing associated costs can promote consumer participation; however, the cost‐reduction‐oriented policies adopted by the Chinese government has had little impact on consumer participation. This study explores the reasons for the failure of the Chinese cost‐reduction‐oriented policies in food safety governance from the perspective of the collective action dilemma. Building upon previous work and using data from an online survey of 1229 consumers in China, we use a mediating effect model to examine the causal relationship between the low participation rate and the high participation cost. The results suggest that low consumer participation in food safety governance is due to free‐riding built on the actions of others. The problem with the cost‐reduction‐oriented policies is that they addressed high participation costs, identified by this study as the consequence of non‐participation, but paid little attention to the actual cause – free‐riding. Our research sheds light on the collective action dilemma from a new perspective to understand consumer participation. Assessing the relationship between participation cost, free‐riding, and the actual participation behavior in food safety governance could lead to a new line of theoretical and empirical inquiry for studying collective action in public affairs.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".