Canadian government policy innovation labs: An experimental turn in policy work?
Bibliographic record
Abstract
Abstract Governments across the globe are searching for new methods to apply to policy work. New Public Governance (NPG) suggests the state's policy process has become more accessible to a broader range of policy actors including non‐state ones. Policy innovation labs speak to this turn to broadening inputs and to methodological experimentation. The focus of this article is to provide an overview of Canadian government policy innovation labs (GPILs) operating in this relatively new space. Despite the ascent of GPILs, they remain, especially in the Canadian context, much understudied. Exploring a select number of Canadian government policy labs operating at the federal, provincial and municipal levels, we provide some insights into their work.
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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 | 0.076 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.030 | 0.037 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.018 | 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".