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Record W2186341791

Climate Change and Canadian Unions: The Dilemma for Labour

2022· report· en· W2186341791 on OpenAlexaffabout
Carla Lipsig-Mummé, Geoff Bickerton

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typereport
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsYork University
Fundersnot available
KeywordsDilemmaPolitical scienceContext (archaeology)Political economyWork (physics)PoliticsGlobal warmingGovernment (linguistics)Climate changePolitical economy of climate changeCollective bargainingPessimismSociologyLawGeography
DOInot available

Abstract

fetched live from OpenAlex

In 2010, a group of Canadian trade unions, labour academics and environmental groups began a five year funded community-university research project, Work in a Warming World (W3), to develop effective ways for labour to take leadership in the struggle to slow global warming. We stated the problem this way: How can labour broaden and deepen its capacity to protect work and workers from the unique threats posed by climate change, all the while contributing to the struggle to slow global warming within the context of increasingly pessimistic climate science, global economic crisis, a hostile national government and strategic paralysis in the national and international political arena? The authors explore the challenges and dilemmas for labour leadership in relation to environmental responsibility in the current political climate in Canada, drawing on W3 research and the unexpected uses that research can be put to, using the case of the Canadian Union of Postal workers in catalyzing and internationalising activist engagement for climate bargaining.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.220
Teacher spread0.176 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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