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Record W180197751

Class Action: Class, Politics and Union Activists in Alberta

2003· dissertation· en· W180197751 on OpenAlexaboutno aff
Jason Foster

Bibliographic record

VenueMacSphere (McMaster University) · 2003
Typedissertation
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)PoliticsClass actionPolitical scienceAction (physics)Public administrationLawMathematicsComputer scienceArtificial intelligencePhysicsState (computer science)
DOInot available

Abstract

fetched live from OpenAlex

This study explores the link between class and political activism by examining the union and political participation of union activists in Alberta. Through a survey and selected in depth interviews, the study finds union activists are more politically active than average Canadians. It arrives at three core conclusions. First, union activists who possess a relational sense of class consciousness are more likely to engage in political activity. This class consciousness is formed and articulated out of lived experience, rather than intellectual understanding, and can be seen as an expression of a "culture of solidarity". Second, union activists experience a perceptible class divide separating them from middle class institutions of the political system. This divide can inhibit political participation. Union activists who cross the divide into middle class politics can be seen as "bridge builders", linking working class activists with middle class political culture. Third, unions can play an important role in fostering political activism among their members. Unions can influence the decision to act politically through concrete local action and framing the nature of union work in a class relational fashion. Recommendations for union strategies are offered, as well as suggestions for revitalizing progressive political organizations.

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)0.001
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 score0.034
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.015
GPT teacher head0.254
Teacher spread0.238 · 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
Published2003
Admission routes1
Has abstractyes

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