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Record W1557571374

Organized Labour and Local Politics: Ontario’s 2006 Municipal Elections

2008· article· en· W1557571374 on OpenAlexaffvenueabout
Larry Savage

Bibliographic record

VenueLabour / Le Travail · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsBrock University
Fundersnot available
KeywordsPoliticsRestructuringPublic administrationPolitical scienceDemocracyLocal governmentPolitical machinePolitical economyGovernment (linguistics)Economic restructuringEconomic growthSociologyEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

On 13 November 2006, a record number of labour-endorsed candidates were elected to municipal councils and local school boards in Ontario’s municipal elections. Although the labour movement’s foray into municipal politics was not altogether new,1 the 2006 elections in Ontario represented a strategic shift in the political priorities of organized labour. For years, unions in English Canada had placed the bulk of their political resources squarely behind the electoral efforts of the New Democratic Party (ndp) at both the federal and provincial levels. However, campaign finance reform at the federal level, combined with unprecedented municipal downloading, and neoliberal economic restructuring, have forced the labour movement to rethink its approach to electoral politics. In short, the Canadian Labour Congress (clc), Canada’s largest labour central, has identified municipal politics as an area worthy of unprecedented attention and resources. Although a focus on municipal politics may offer the labour movement new opportunities to promote its agenda more effectively, the structure and political culture of local government also present tremendous obstacles for advancing the goals of organized labour. This article begins with a description

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)0.003
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 score0.095
Threshold uncertainty score0.687

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0150.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.014
GPT teacher head0.248
Teacher spread0.233 · 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

Citations4
Published2008
Admission routes3
Has abstractyes

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