Searching for strategy: Value for Money (VFM) audit choice in the new public management era
Bibliographic record
Abstract
Abstract Value for Money (VFM) audits are now critical aspects of accountability in Westminster systems, based on the assumption that ministries are systematically examined. This study explores the VFM inquiries of the Auditor General of Ontario (AGO) between 1997 and 2014 as a case study to uncover trends of consistency of approach under the flourishing “new public management” philosophy of cutting costs and raising efficiencies. It asks three broad questions: does the frequency and intensity of VFM audits correlate with the financial importance of the ministries? Do political controversies affect the choice of what will be subject to a VFM audit? Finally, do Auditors General make a personal difference in what ministries will be audited through a VFM framework? The findings demonstrate a pattern of over‐auditing of some ministries while important ministries are consistently under‐audited.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".