Analyzing Recent Citizen Participation Trends in Western New York: Comparing Citizen Engagement Promoted by Local Governments and Nonprofit Organizations
Bibliographic record
Abstract
Engaging citizens in the decision-making process is becoming an important priority for many local governments. This article evaluates three citizen engagement events in two jurisdictions in western New York: public forums held by the Buffalo Fiscal Stability Authority, Citizen Participation Academy, and Participatory Budgeting Project. Using in-depth interviews with public and nonprofit employees, the article outlines several findings, including a distinctly higher level of effectiveness of engagement strategies when advanced by not-for-profit organizations. The engagement initiated by state and municipal governments reflects authoritarian and bureaucratic models of participation. This study highlights several challenges to the sustainability of citizen involvement at municipal levels, and its results have important implications for other towns implementing participatory tools. RÉSUMÉ Pour plusieurs gouvernements locaux, l’engagement des citoyens dans la prise de décision devient prioritaire. Cet article examine cette situation en évaluant trois événements portant sur l’engagement des citoyens dans deux juridictions de l’ouest de l’État du New York, à savoir des forums publics organisés par le Buffalo Fiscal Stability Authority, le Citizen Participation Academy et le Participatory Budgeting Project. Au moyen d’entrevues en profondeur auprès d’employés des secteurs public et sans but lucratif, cet article fait plusieurs constats, y compris celui d’une efficacité beaucoup plus grande des stratégies d’engagement suivies par les organisations sans but lucratif. En revanche, l’engagement sollicité par les gouvernements des États et des municipalités reflète des modèles de participation relativement autoritaires et bureaucratiques. Cette étude souligne plusieurs défis soulevés au niveau municipal par les tentatives d’inclure la citoyenneté. Les résultats de cette étude ont des implications importantes pour d’autres villes qui s’efforcent d’encourager la participation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".