What has become of the audit explosion? Analysing trends in oversight activities in the Canadian Government
Bibliographic record
Abstract
Since the 1980s, many governments expanded their administrative oversight systems, such as auditing and evaluation, in order to improve the efficiency, performance and accountability of their administration. Yet few studies empirically examine this “audit explosion”. Our study investigates its more recent manifestation. Using Canada as an exploratory case, we first assess whether the level of these oversight activities contracted or expanded in the last two decades. We then analyse the contents of 3245 audit reports published between 2000 and 2019 to track changes in the focus of auditing. Results suggest that, while the overall level of administrative oversight is much higher now than in 2000, it grew only in the first decade of the millennium and was confined to internal functions, namely departmental audits and evaluations, as opposed to the country's Supreme Audit Institution. Meanwhile, auditors’ attention to financial matters declined, while their focus on compliance, performance and risk increased.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.012 | 0.028 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".