The Politics of Public Management: The HRDC Audit of Grants and Contributions
Bibliographic record
Abstract
The Politics of Public Management: The HRDC Audit of Grants and Contributions, David A. Good, The Institute of Public Administration of Canada Series in Public Management and Governance; Toronto, University of Toronto Press, 2003, pp. 240 The literature in public administration in some ways suffers from not having more practitioners reflecting, writing and analyzing their experiences. Thus David Good's book analyzing the HRDC's so-called “billion dollar boondoggle” is a welcome contribution. His background as both a senior manager/executive within the Federal government and his academic credentials—a doctorate in policy and administration sets him apart—as a practitioner-academic. Good possesses the senior public manager's mind for detail and this book provides a clear account of the ebbing and flowing of events, beginning with the January 2000 release of HRDC's internal audit that implied a loss of a billion dollars, to the Auditor General's report of October that same year which, while critical of monitoring and reporting practices, concluded that only $85,000 was unaccounted for. The media and the opposition, at this point quickly lost interest.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".