Defying Stereotypes, Populism, and Neoliberal Discourse: Municipal Agility and Innovation During COVID
Bibliographic record
Abstract
Local governments are often viewed as basic service and infrastructure providers that are neither particularly proactive nor innovative: in certain influential circles, this view has taken on the trappings of “common-sense,” and underpins the protracted undermining of public-sector organizations, a hallmark of neoliberalism. However, the COVID crisis required municipalities to act with agility and speed, belying this “common sense.” We examine 54 examples of how municipalities in Québec adapted to the pandemic. The range of adaptation and innovation that we report illustrates that local government can be flexible, agile, and innovative when necessary. Our analysis suggests that innovation is not always desired by the innovator, that the impact of a project should be distinguished from its innovativeness, and that any assessment of municipal innovativeness and its impact requires careful consideration of who it is evaluated for, who it is evaluated by, and in what context.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".