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Wall-to-wall worker organizing in the university: the Coalition of Rutgers Unions

2024· article· en· W4405312531 on OpenAlexafffund
Paul Christopher Gray, Jordan House

Bibliographic record

VenueWork in the Global Economy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsBrock University
FundersCouncil for Research in the Social Sciences, Brock University
KeywordsCruPolitical scienceCertificationPublic administrationState (computer science)Political economySociologyPublic relationsManagementLawEconomics

Abstract

fetched live from OpenAlex

Workers at Rutgers University, the state university of New Jersey, US, have formed the Coalition of Rutgers Unions (CRU). This workplace-based union coalition engages in wall-to-wall organizing, which seeks to include every Rutgers worker, irrespective of occupation, status, or union affiliation. This form of coalition creatively retains the benefits of certified unions while navigating the sectionalism encouraged by American labour laws. CRU’s recovery of traditional organizing principles amid neoliberal conditions is a new industrial unionism. It is thereby an example of the union renewal affirmed by proponents of social movement unionism. CRU is also an organizational model for workers in large, complex, heterogeneous workplaces with multiple existing unions. This article draws from qualitative interviews with CRU activists to discuss its participants, structure, activities, and its role in a victorious 2023 strike at Rutgers University.

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)0.007
metaresearch head score (Gemma)0.007
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 score0.038
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0330.017
Scholarly communication0.0100.006
Open science0.0030.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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