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Record W2139284912 · doi:10.1177/0950017010380644

Working at McDonalds: some redeeming features of McJobs

2010· article· en· W2139284912 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.

Bibliographic record

VenueWork Employment and Society · 2010
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWorkforceBusinessMarketingWork (physics)Service (business)Human resource managementSample (material)Public relationsManagementEconomicsPolitical scienceEconomic growthEngineering

Abstract

fetched live from OpenAlex

Within much critical research literature, fast-food jobs are presented as offering few employee advantages. Indeed the disparaging term ‘McJob’ has come to describe low-skill, low-pay, dead-end, routine service industry employment in general. In contrast, there is employer-oriented literature that portrays fast-food jobs more positively and even presents them as beneficial for the workforce. This study analyses survey data from a sample of Australian McDonald’s outlets to determine employee and employer experiences and attitudes towards these so-called McJobs. Findings indicate that employees view their jobs as consisting of repeatedly doing a limited range of non-complex tasks whereas managers perceive aspects of the job more positively. Evidence is presented that fast-food jobs offer human resource advantages, potential career opportunities and, for some, desirable forms of work organisation. These findings suggest that the current, dominant portrayal of McJobs is inaccurate, with the reality more nuanced.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.351
Teacher spread0.315 · 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