Assessing the effects of an Intelligence Performance Regime: Quebec's <i>Municipal Management Indicators</i> , 1999–2010
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Quebec's Municipal Management Indicators embodies what Hood (2007) described as an intelligence regime. This research tries to determine if the design of the municipal intelligence performance regime in Quebec, Canada, delivered the expected results. To answer that question, publicly available official documents, minutes of meetings, and survey data are used. The story of Quebec's regime offers a counter-example to Pollitt and colleagues’ (2010) theory that once in place, performance regimes follow a logic of escalation. The municipal intelligence regime in Quebec never moved from formative to summative; from intelligence to targets and rankings. The experience in that Canadian province offers support to Hood's (2007) model about the shortcomings of intelligence regimes. Points for practitioners The case study of a performance regime details an effort with few demands on participants. It is argued that the documented shortcomings are the result of the strategic path initially taken by decision makers, not the result of their later decisions and adjustments. Shielded from public scrutiny and without sanctions from the provincial government, most municipal managers chose not to use the indicators, not to include them in budgets and annual reports, not to compare themselves to others, and not to set targets for themselves. In a mandated regime with bottom-up and voluntary approaches, most municipalities effectively opted out.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 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 it