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Record W4409552382 · doi:10.1177/07308884251334667

Labor Games, Citizenship, and Control: Book Review Essay of Weststar &amp; Legault and Wu Legault, M. and Weststar, J. (2024). <i>Not All Fun and Games: Videogame Labour, Project-based Workplaces, and the New Citizenship at Work</i> . Montreal: Concordia University Press. 464 pp. $49.69 (paper).Wu, T. (2024). <i>Play to Submission: Gaming Capitalism in a Tech Firm</i> . Philadelphia: Temple University Press. 245 pp. $30.95 (paper).

2025· article· en· W4409552382 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWork and Occupations · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipSociologyControl (management)Labour economicsGender studiesEconomicsManagementLawPolitical science

Abstract

fetched live from OpenAlex

As the game and tech industries face ongoing challenges, such as layoffs, employee overwork, and burnout, as well as responses, such as rising pushes for unionization, we have seen increasing amounts of scholarly work on these industries and their workers. Many existing studies, however, emerge from media studies, game studies, and cultural industries spaces, meaning they tend to theorize the game industry through these lenses, rather than engaging existing research in labor and occupation studies. The two books reviewed here begin the process of marrying these fields more closely, using theories of citizenship at work and labor games to explore worker agency and structural constraints in the game and tech industries. This review essay summarizes both titles and provides an overview of their strengths and weaknesses. It concludes that both books provide excellent additions to the field of game production studies, promoting new approaches to understanding what work does and could look like in these industries.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.249
Teacher spread0.235 · 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