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Record W4388586948 · doi:10.52975/llt.2023v92.003

Waitresses in Action

2023· article· en· W4388586948 on OpenAlexaffvenueabout
Joan Sangster

Bibliographic record

VenueLabour / Le Travail · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsTrent University
Fundersnot available
KeywordsFeminismPublicityAutonomyGovernment (linguistics)Gender studiesPolitical scienceDignityAction (physics)SociologyLaw

Abstract

fetched live from OpenAlex

In the 1970s, women in Toronto created the Waitresses Action Committee to protest the introduction of a “differential” or lower minimum wage for wait staff serving alcohol. Their campaign was part of their broader feminist critique of women’s exploitation and the gendered and sexualized nature of waitressing. Influenced by their origins in the Wages for Housework campaign, they stressed the linkages between women’s unpaid work in the home and the workplace. Their campaign eschewed worksite organizing for an occupational mobilization outside of the established unions; they used petitions, publicity, and alliances with sympathizers to try to stop the rollback in their wages. They were successful in mobilizing support but not in altering the government’s decision. Nonetheless, their spirited campaign publicized new feminist perspectives on women’s gendered and sexualized labour, and it contributed to the ongoing labour feminist project of enhancing working-class women’s equality, dignity, and economic autonomy. An analysis of their mobilization also helps to enrich and complicate our understanding of labour and socialist feminism in this period.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.182
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0170.005
Scholarly communication0.0050.001
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0630.006

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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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