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Record W2969607518 · doi:10.36939/cjur/vol26no2/art95

Citizen Participation in the Public Transportation Policy Process: A Comparison of Detroit, Michigan, and Hamilton, Ontario

2017· article· en· W2969607518 on OpenAlexaffvenueabout
John B. Sutcliffe, Sarah Cipkar

Bibliographic record

VenueCanadian journal of urban research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRepresentativeness heuristicPublic administrationCitizen journalismJuryPolitical sciencePublic participationPopulationPoliticsSociologyLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.156
GPT teacher head0.454
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2017
Admission routes3
Has abstractyes

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