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Record W3005290692

Education For Changing Unions

2002· book· en· W3005290692 on OpenAlexaboutno aff
Bev Burke, D’Arcy Martin

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsCraftWork (physics)Political sciencePublic relationsPower (physics)Trade unionPublic administrationSociologyEngineeringEconomicsLabour economicsGeography
DOInot available

Abstract

fetched live from OpenAlex

This publication gathers together the collective experiences of educators working in Canada’s labour movement and considers three dimensions of union education: the job of union education itself; the craft of union education; and the ways in which union education can employ education as a strategy for change. Part one describes the job of union education and situates it in the union culture. Part two considers the craft of union education and covers program design, successful workshop activity planning, favourite union education activities, facilitation to achieve objectives of education sessions and move social change work forwards, and the power of co-facilitation. Part three considers how union education might strengthen democracy and participation across unions in terms of organisational practices. A framework and strategies for evaluating union education work and ways of developing worker educator programs are discussed. Strategic planning initiatives are also covered along with how education can strengthen them. This section concludes with some thoughts on how to do such work over a long period of time without burning out.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.299
Threshold uncertainty score0.595

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.005
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0290.004

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 head0.029
GPT teacher head0.317
Teacher spread0.288 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations22
Published2002
Admission routes1
Has abstractyes

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