Auditing citizen engagement in heritage planning: The views of citizens
Bibliographic record
Abstract
Abstract: Drawing the citizen back into public fora has become the issue of the day in democratic countries around the globe. On the political stage, there is growing alarm over a perceived “democratic deficit,” which has inspired a variety of innovative means of engaging citizens in public policy decisions. This plethora of engagement mechanisms invites the question of how citizens evaluate these engagement opportunities, a question that reveals a decided lacuna of studies regarding citizen assessments of these various mechanisms. This study is a report from the citizen participants on the merits of a Nova Scotia model of citizen engagement in policy development. It examines a citizen task force organized by Voluntary Planning, which conducted a citizen consultation process to create policy recommendations for heritage preservation in Nova Scotia, using its distinctive technique of citizen engagement. This study is the first evaluation of the Nova Scotia process from the perspective of citizen participants conducted to date. It concludes that the process used is highly regarded and enhances the legitimacy of such mechanisms as the “voice of the people” for citizens themselves and government decision‐makers.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".