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Record W2273238158

Participatory Democracy and Decentralization Processes: A Comparison between Marseilles (France), Montreal and Quebec (Canada)

2011· article· en· W2273238158 on OpenAlexaffabout
Caroline Patsias

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsDecentralizationPublic administrationCitizen journalismDemocracyTechnocracyPoliticsPolitical scienceBlueprintArgument (complex analysis)SociologyPolitical economyLawEngineering
DOInot available

Abstract

fetched live from OpenAlex

The aim of this paper is to examine the links between certain processes and forms of decentralization and the emergence of participatory arrangements. More specifically, the paper will address the question: under what conditions are certain forms of decentralization conducive to a genuinely more participatory democracy? The argument rests on a comparison between three participatory designs in Marseille, Montreal and Quebec. Has decentralization encouraged participatory democracy in each of these cases? The comparison deploys two intersecting analytical approaches: - Territorial: These participatory bodies are to various degrees part and parcel of decentralization reforms at different scales (local, regional, and national). Are the participatory bodies explicitly connected to the decentralizing project spelled out in the legislation or are they the consequence of a new opportunity window? What is the interplay of actors (political parties, social movements, civil servants) and at what levels? What strategies does the periphery adopt in order to redesign the projects developed at the centre? How can one explain the fact that they remain at the local or infra-local level, even when they are the product of reforms at the centre? - Historical: the partipatory idea emerged long before the late 1990s. How do decentralizing reforms that offer blueprints of these new sites of participation relate to older projects? Some of the analyses underpinning this paper date back to the 1970s

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.962

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0100.006
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.034
GPT teacher head0.262
Teacher spread0.227 · 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 designQualitative
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

Citations0
Published2011
Admission routes2
Has abstractyes

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