1198 Is scientific inquiry incompatible with government information control?
Bibliographic record
Abstract
and Richard L. Haedrich Abstract: Government-administered science in Canada, and its potential for bureaucratic and political interference, merits examination in the wake of the biological and socioeconomic catastrophes associated with recent fishery collapses. We cite specific research on Atlantic cod (Gadus morhua) and Pacific salmon (Oncorhynchus spp.) habitat to illustrate how nonscience influences can interfere with the dissemination of scientific information and the conduct of science in the Canadian Department of Fisheries and Oceans. The present framework for linking fisheries science with fisheries management has permitted, intentionally or unintentionally, a suppression of scientific uncertainty and a failure to document comprehensively legitimate differences in scientific opinion. We suggest that the conservation of natural resources is not facilitated by science integrated within a political body. The formation of a politically independent organization of fisheries scientists, or some such reorganization of the link between scientific research and the management of natural resources, merits serious and open debate. Résumé: La science administrée par le gouvernement au Canada, et sa vulnérabilité à l’intervention bureaucratique et politique, doit faire l’objet d’un examen à la suite des catastrophes biologiques et socio-économiques liées à l’effondrement récent des pêches. Nous citons de la recherche spécifique sur la morue franche (Gadus morhua) ainsi que l’habitat du saumon du Pacifique (Oncorhynchus spp.) pour démontrer comment des interventions non scientifiques peuvent gêner la diffusion de l’information scientifique et la conduite de la science au ministère des Pêches et des Océans du Canada. Le cadre de travail
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 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 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.033 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".