Environmental Regulation and the COVID-19 Pandemic: A Review of Regulator Response in Canada
Bibliographic record
Abstract
Governments worldwide weakened environmental protection in response to the COVID-19 pandemic, including federal and provincial government agencies across Canada. In this briefing paper, I review and analyze these actions, comparing the types of rules changed, types of changes, rationale and sectors impacted. Results show that Canadian regulators took one of two approaches: enforcement discretion or pre-emptive rule adjustment. Industry, government and public stakeholders all benefited from relaxed rules. Most of the rules relaxed, however, were specific to certain industrial sectors: the oil, gas and coal; mining; fisheries and water sectors. Regulators’ main reason for adjusting environmental rules was to address capacity constraints faced by regulated entities, with limited detail provided to justify the changes in most cases. Over a third of the changes were indefinite with no set end date. I discuss implications of these actions, including increased risk of harm to the environment and human health, budgetary impacts, noncompliance enforcement and considerations for regulatory design moving forward.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".