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Record W1592763322

Unionizing Retail: Lessons From Young Women's Grassroots Organizing in the Greater Toronto Area in the 1990s

2011· article· en· W1592763322 on OpenAlexaffabout
Kendra Coulter

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRetail industryWork (physics)Retail tradeGrassrootsCapitalismLivelihoodAppealBusinessLabour economicsPolitical scienceEconomicsAgricultureMarketingGeographyLawEngineeringCommercePolitics
DOInot available

Abstract

fetched live from OpenAlex

Unionization in the retail sector is not well researched or understood and the work of everyday organizing in retail sites is rarely discussed. This is surprising since the most common occupation for both women and men in Canada is now retail salesperson/clerk.1 Furthermore, retail work continues to be characterized by low wages, few, if any, benefits and job insecurity. Despite these conditions and the rapid growth of retail work as an area of employment, this sector remains one of the most unorganized in the Canadian labour force. In 2009, 29.5 per cent of Canadian workers were represented by a union but only about twelve per cent of retail workers were union members.2 Within the retail sector, unionized workers are concentrated in food retail/grocery and warehouse work.3 As a contribution to the larger project of understanding the challenges and possibilities of organizing retail workers, I examine two retail unionization drives in the Greater Toronto area in the 1990s which were led by young women. During this period of neoliberal capitalism, material and ideological attacks on labour unions and working-class livelihoods and identities were widespread. However, unionization continued to appeal to many workers who

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.681
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.251
Teacher spread0.199 · 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.

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

Citations6
Published2011
Admission routes2
Has abstractyes

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