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Record W2947701139 · doi:10.1177/1527476419851087

Building Momentum for Collectivity in the Digital Game Community

2019· article· en· W2947701139 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTelevision & New Media · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité TÉLUQWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCollective actionMobilizationPublic relationsSociologyEquity (law)Video gamePower (physics)Political sciencePolitical economyMedia studiesComputer scienceMultimediaPoliticsLaw

Abstract

fetched live from OpenAlex

Studies of digital game labor have tended to document problems in the working lives of developers while devoting relatively limited attention to solutions, or to collective representation as a step toward solutions. An increasing number of game developers are dissatisfied with their working conditions, and dissatisfaction is a necessary condition for workers to engage in collective action to gain the representational power needed to achieve change in the workplace. Noting that the landscape of collective mobilization in the game industry has not yet been systematically mapped, this article documents collective actions over the past five decades, and asks, “Are the collective actions of developers building momentum toward a viable, sustained mobilization?” The article presents a thematic survey of such actions, including the Quality of Life Movement, exposés of working conditions, gender equity struggles, and unionization efforts. In conclusion, the authors revisit John Kelly’s mobilization theory to assess developers’ capacity to engage in collective mobilization.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.322
Teacher spread0.280 · 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