Citizen Participation in the Public Transportation Policy Process: A Comparison of Detroit, Michigan, and Hamilton, Ontario
Bibliographic record
Abstract
This paper provides a comparative analysis of citizen participatory mechanisms used within transit planning. This research focuses on two cities that institutionalized citizen participation through a Citizens Advisory Committee (CAC) in Detroit, Michigan, and a Citizens’ Jury (CJ) in Hamilton, Ontario. The paper analyzes their overall representativeness of the general population, their operation and level of ‘policy learning’ that occurs within their group, and their impact on subsequent transit policies. We find that these participatory mechanisms are generally regarded as important and useful by both the participants and the politicians that established them. In spite of this, the conclusion reached is that neither mechanism had a significant impact on transit policies. In both cases, the policy decisions were affected by a range of factors and particularly the local and regional political contexts. Indeed, it can be argued that both cities are plagued with regional divides which potentially no amount of citizen participation can solve.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".