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Record W1978043777 · doi:10.1177/1077800411431555

An Ethnodrama on Work-Related Learning in Precarious Jobs

2012· article· en· W1978043777 on OpenAlex
Jasjit Kaur Sangha, Bonnie Slade, Kiran Mirchandani, Srabani Maitra, Hongxia Shan

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueQualitative Inquiry · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of CalgaryYork UniversityUniversity of Toronto
Fundersnot available
KeywordsResistance (ecology)SociologyWork (physics)Embodied cognitionStereotype (UML)Ethnic groupRace (biology)Gender studiesPublic relationsSocial psychologyPsychologyPolitical scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

This article is based on a research project on the lived experiences of precarious workers in Toronto, Canada. Using interviews with women in part-time, contract, and temporary jobs in three sectors (telemarketing, retail, and garment), the project explores the ways in which racial hierarchies structure jobs as well as forms of resistance that women exercise at work. The authors find that racialized processes stereotype workers and their skill sets, organize their work, determine their access to and exclusion from certain types of jobs, and impose cultural rules that classify and essentialize them in terms of race, language, and ethnicity. In this article, the authors use ethnodrama to represent their findings from this research project. Ethnodrama is a form that is well suited for this work because it allows us to bring the data to life through an embodied performance.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.179
GPT teacher head0.526
Teacher spread0.346 · 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