Extirpation despite regulation? Environmental assessment and caribou
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Many caribou populations in Canada face extirpation despite dozens of provincial and federal legislative instruments designed to protect them. How are industrial developments that impact caribou justified and permitted despite governments' commitments to caribou protection? Toward an answer, this paper scrutinizes an approval process for major projects in Canada: environmental assessment (EA). We identify 65 EAs for major projects with potentially significant adverse impacts for caribou—all projects but one were approved. The results show that most projects were approved on the basis of proposed mitigation measures that promise to render adverse effects “insignificant”; yet mitigation effectiveness is largely unknown. Further, several projects were approved even though mitigation measures were insufficient, citing public or national interest. Finally, some projects' approval rested in part on scientific claims that the project area is already degraded or absent of caribou. Based on these findings, EA is failing caribou, acting as a means by which the state licenses major developments with potentially significant adverse effects for caribou, with a pretense of protection. The failure stems in part from a broader tension within the state that manifests in EA: a tension between the state's roles promoting economic growth and protecting against this growth's negative effects. Recognition of this tension needs to be more central to conservation biology.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it