A study in executive branch noncompliance with law : government secrecy, endangered species protection, and the whitebark pine
Bibliographic record
Abstract
The Access to Information Act, Canada’s law for the public accessibility and secrecy of government records, came into force in 1983. The Species at Risk Act, Canada’s law for endangered species protection came into force in 2003. Neither of the two laws have fulfilled their intended goals. This thesis investigates the causes of the ‘slippage’ between these laws as written and as implemented. This thesis compares the decades of implementation of these two laws to the texts of the laws and the intentions of the legislators who wrote them and finds deliberate and routine executive branch noncompliance has been a major cause of the failures of the laws to achieve their intended goals. The research methodology includes the use of records obtained using a request filed under the Access to Information Act relating to Environment and Climate Change Canada’s long delay in preparing a final Recovery Strategy for the endangered Whitebark Pine. These records are used to illustrate the problem of executive branch noncompliance with law. The thesis analyzes why neither the judicial branch nor Canada’s democratic system are able to prevent or stop executive branch noncompliance and argues that Canada’s traditional system of cabinet confidentiality and secret bureaucratic advice to ministers undermines the rule of law and democracy. The thesis calls for recognition of executive branch secrecy and executive branch noncompliance with law as major obstacles to the rule of law and democracy in Canada.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.023 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".