Creating a Strong Disclosure-of-Wrongdoing Regime: The Role of the Public Service Integrity Officer of Canada
Bibliographic record
Abstract
Canada enacted the Public Servants Disclosure Protection Act in 2006, nearly a decade after the United Kingdom and its former colonies Australia and New Zealand enacted whistle-blowing legislation, and almost two decades after the United States. Canada's law was unique in its comprehensiveness and in providing access by public servants and private citizens to an independent agent of Parliament, the public service integrity officer, who is exclusively responsible for investigating and resolving allegations of wrongdoing and protecting from reprisal those who make disclosures (with the provision of a tribunal to settle and remedy reprisal complaints not resolved by conciliation). This article is a study of the role of the public service integrity officer in creating a stronger disclosure-of-wrongdoing regime. It documents the impact of four years of advocacy with three different governments that in no small part contributed to a shift from a narrow, policy-based office with limited authority to a broad, legislatively created office with expansive authority. This successful example of knowledge speaking to power fortuitously coincided with the desire of the Liberal Party to use whistle-blowing legislation to blunt the political damage caused by the Sponsorship Scandal and the subsequent interest of the Conservative Party in making the Public Servants Disclosure Protection Act the centerpiece of the Federal Accountability Act to clean up government and restore integrity.
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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 | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.043 | 0.032 |
| Scholarly communication | 0.021 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".