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Record W2925189897 · doi:10.1177/1440783319833188

Retail therapy: Making meaning out of menial labour

2019· article· en· W2925189897 on OpenAlexafffundabout
Genevieve Johnston, Matthew D. Sanscartier, Matthew S. Johnston

Bibliographic record

VenueJournal of sociology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrivilege (computing)SociologyCapitalismMeaning (existential)Gender studiesWorking classEthnic groupSet (abstract data type)Consumption (sociology)Work (physics)Social psychologyPolitical sciencePoliticsPsychologySocial scienceLawEngineering

Abstract

fetched live from OpenAlex

Retail work has a prominent place in the Canadian job market in an era of global capitalism and consumption. Despite spanning an astonishing array of industries, this work is most often low-paying, low-status and un-unionized, leaving workers vulnerable to exploitation and discrimination from their employers. This qualitative content analysis of 1454 anonymous reviews of 25 Canadian retail employers posted on RateMyEmployer.ca explores how intersections of class, race and gender shape how workers make sense of difficult work experiences and their relative social privilege. We draw on Hewitt and Hall’s concept of quasi-theorization to frame how everyday experiences of work justify foregone conclusions that allow reviewers to reassert status. Set against highly gendered, raced and classed expectations of the helpful, deferential, hardworking and cheerful retail worker, these quasi-theories demonstrate that ethnic and racial bias, reactive masculinities and battles between working-class supervisors and middle-class student employees lead to unresolved friction that erupts in anonymous, online spaces.

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)0.012
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 score0.181
Threshold uncertainty score0.360

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0270.042
Scholarly communication0.0140.006
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.066
GPT teacher head0.388
Teacher spread0.322 · 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

Citations3
Published2019
Admission routes3
Has abstractyes

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