Inclusive and Participatory Policymaking at the Local Level: Problems and Possibilities
Bibliographic record
Abstract
Municipalities are being called on to become more participatory in their approach to policy making and governing. Concurrently, they are working toward making their policies, programs, and staff complements more inclusive and equitable, and more responsive to the ongoing consequences of colonialism and other forms of systemic discrimination. These developments share common normative and theoretical foundations, but municipalities are not necessarily actively working on these changes in tandem. In response, we ask, “What are the problems and possibilities that emerge in efforts to centre Indigenous Knowledges and intersectional commitments in participatory policymaking processes at the local level?” We highlight two barriers that arise persistently in these efforts and suggest modest ways forward that will be useful for municipal public servants working on community engagement; diversity, equity, inclusion efforts; and building relationships with Indigenous residents.
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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 | 0.072 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.048 |
| Scholarly communication | 0.029 | 0.021 |
| Open science | 0.004 | 0.029 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".