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Record W2997527272 · doi:10.1002/ace.20354

Activist Learning and Temporary Agency Workers in Quebec

2019· article· en· W2997527272 on OpenAlexaffabout
Manuel Salamanca Cardona, Aziz Choudry

Bibliographic record

VenueNew Directions for Adult and Continuing Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsMcGill University
Fundersnot available
KeywordsAgency (philosophy)SociologyImmigrationCommunity organizingEthnographyAdult educationPublic relationsResistance (ecology)Economic JusticeWork (physics)Vulnerability (computing)Political sciencePublic administrationPedagogySocial scienceLaw

Abstract

fetched live from OpenAlex

Abstract This chapter addresses learning and nonformal education in the course of organizing migrant and immigrant (im/migrant) temporary agency workers through the Immigrant Workers Centre (IWC) and the Temporary Agency Workers Association (TAWA) in Montreal. The IWC/TAWA organizing approach with agency workers is based on community organizing, activist knowledge production, popular education, and leadership development. Activist education work has helped to foster sustained organizing and campaigns against exploitation by temp agencies in Quebec. This has led to important gains like a recently adopted law that includes several provisions to regulate agencies. We build on critical ethnographic activist research, radical adult education literature concerning social movements, and apply Freire's concepts of limit situations and untested feasibility to TAWA/IWC organizing approaches. We argue that precarious work entails both vulnerability and resistance, and suggest that researchers should attend to the role of activist education, learning, and knowledge production to better understand social and economic justice struggles.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.000

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 head0.007
GPT teacher head0.286
Teacher spread0.280 · 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

Citations5
Published2019
Admission routes2
Has abstractyes

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