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Record W3008544167 · doi:10.18740/ss27273

Racism as a Workload and Bargaining Issue

2020· article· en· W3008544167 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSocialist studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRacismArgument (complex analysis)WorkloadHarassmentCollective bargainingIndigenousSociologyPsychometrics of racismPublic relationsPolitical scienceGender studiesLawManagementEconomicsMedicine

Abstract

fetched live from OpenAlex

My main contention is that racism should be read beyond the registers of discrimination, human rights, or harassment – rather, I approach racism as a workload issue that labour organizations and employers need to address at the level of collective bargaining. To illustrate this argument, I focus on racism and workload as it relates to Black faculty, faculty of colour, and Indigenous faculty in universities and colleges in Canada, although the argument can be applied to other job types and other places. While many unions have policies and statements in support of local, national and international anti-racist struggles, the idea of racism as a workload issue has not been seriously taken up by unions/associations, or for that matter by anti-racist activists on university/college campuses. I offer reasons why racism is a workload issue, and consider the potential role of unions in addressing racism.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.073
GPT teacher head0.394
Teacher spread0.321 · 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