Silences and Lies: How the Industrial Fishery Constrained Voices of Ecological Conservation
Bibliographic record
Abstract
In combination with historical research, this paper uses interviews of fishers, fishery workers, scientists, and Canadian Department of Fisheries and Oceans (DFO) enforcers and observers to recount the communication processes that occurred before the 1992 collapse of the cod fishery in Atlantic Canada. As the fishery industrialized over the course of the twentieth century, those who worked in the industry became increasingly segregated. Distinct discursive realms emerged, among them "fishers' vernacular," "scientific language," "product talk," and DFO's "official word." There was little dialogue between the groups and little collective opposition to the overfishing. DFO's "official word" claimed that the stocks were strong despite protestation to the contrary from several fishers' groups and DFO's own scientists. The outcome for the region was economically and ecologically devastating.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.031 | 0.052 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| 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".