Project Review Under Canada’s 2012 <i>Fisheries</i> <i>Act</i>: Risky Business for Fisheries Protection
Bibliographic record
Abstract
Abstract Canada’s Fisheries Act provides essential protection for fish and their habitat. To manage thousands of projects a year, Fisheries and Oceans Canada implements a risk-based framework requiring authorization and offsetting for the highest risk projects. Projects considered lower risk proceed via letters of advice. Following changes to the Act in 2012, there were concerns about transparency and cumulative effects of low-risk projects. We used access to information requests to obtain documents and reviewed the department’s 2012–2019 risk-based framework. Projects reviewed in Manitoba in 2016 were examined and the amount of permanent alteration and destruction approved without authorization was quantified (23,881 and 6,768 m2, respectively). The risk-based framework focused reviews and regulatory decisions on project-by-project effects, rather than cumulative risks from multiple projects. Harm from lower risk projects was not tracked or offset. New mechanisms are needed to manage such projects to achieve the conservation purpose of the Act.
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 | 0.056 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".