Square Peg in a Round Hole? Three Case Studies into Institutional Factors Affecting Public Service Whistleblowing Regimes in the United Kingdom, Canada, and Australia
Bibliographic record
Abstract
Whistleblowing is an important prosocial activity, one which facilitates the early detection and correction of misconduct and deters future misconduct.Recognizing this, many governments have signalled its legitimation by enacting legal protections for public sector whistleblowers, including in the Westminster governments of the United Kingdom, Canada, and Australia.The success of whistleblowing regimes in these jurisdictions is contested, however, as mismanaged programs and retaliation against whistleblowers continue to make headlines.This presents a conundrum.Previous studies have established that if failures accumulate and visible successes are few, employees will lose trust in the regime and use it less, if at all.This would constitute a public policy failure and undermine the implicit long-term goal of improved governance.Departing from previous research approaches, this dissertation uses historical and rational choice institutional theory to test the hypothesis that whistleblowing regimes are born of crisis, but the extent to which they are effectively implemented is dependent on ongoing bureaucratic and political support.This support is contingent upon the regime being consistent with existing institutional arrangements and incentives.When it is not, dysfunctional responses to whistleblowing will continue.Three case studies are presented in order of regime enactment, with the United Kingdom in 1998, Canada in 2005, and Australia in 2013.Process tracing was used to examine three embedded units of analysis: pre-regime institutional development, whistleblowing regime implementation, and the factors effecting regime performance.1 In Canada, this includes Dr. Peter Bryce.Chief medical officer in the federal Department of Indian Affairs, Bryce produced a damning report on the conditions in residential schools in 1907.His report was suppressed and he was forced into retirement; he published it himself in 1922.Bryce's grave in Ottawa's Beechwood Cemetery is now visited with flowers left in thanks (Deachman, 2015).
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".