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Record W1985538579 · doi:10.1177/1078087408326901

Community Organizations and Local Governance in a Metropolitan Region

2008· article· en· W1985538579 on OpenAlexaffabout
Jean-Marc Fontan, Pierre Hamel, Richard L. Morin, Éric Shragge

Bibliographic record

VenueUrban Affairs Review · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsConcordia UniversityUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsMetropolitan areaCorporate governanceContext (archaeology)Economic growthLocal communityLocal economic developmentCompetition (biology)Local governancePovertyCommunity developmentGlobalizationBusinessPublic administrationPolitical scienceEconomicsGeography

Abstract

fetched live from OpenAlex

In a context of globalization, municipalities and metropolitan regions are involved in international competition to support economic growth. This leads to new forms of collaboration between public authorities and businesses, giving birth to new forms of urban and metropolitan governances. Moreover, many old neighborhoods of the central city and some districts of the old suburbs face growth in unemployment and poverty. In these local territories, community organizations put forward local development practices that aim to improve living conditions. These organizations cooperate with other community organizations, public institutions and private agencies. Thus, they are embedded in a kind of governance: a local governance. This article, based on the case of the metropolitan region of Montreal, highlights the conception of local development of these community organizations, the local governance in which they participate, and the link between this local governance with the urban and metropolitan ones.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.008
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.298
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2008
Admission routes2
Has abstractyes

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