Government transparency: the citizen perspective and experience with food and health products policy
Bibliographic record
Abstract
Abstract Citizen engagement (involvement of everyday citizens in policy decisions) is now seen as a major component of governance and policy making. Government transparency is a central tenet of citizen engagement. This study was sought by Health Canada in order to learn from citizen groups in other countries about the nature and degree of transparency related to food and health product review in their country. Health Canada anticipated learning from their experiences and perceptions so that it could increase the transparency of its own review and regulatory process. The opinions of a cross‐section of stakeholders in the United States, the European Union (especially the UK), Australia and New Zealand, solicited via an e‐mail survey, were analysed. The results clearly indicate that, in general, respondents do not feel that their food and health product review system is transparent. These opinions varied depending on which of the seven dimensions of transparency was being examined. Of the 64 recommendations tendered for increasing government transparency, the 32 suggestions for improving their own systems were quite different from the 32 made for Health Canada to consider. Collectively, they provide rich insights into the refinement and clarification of the food and health product review process.
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.
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".