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Record W2947597695 · doi:10.1177/1527476419851086

The New Spirit of Capitalism in the Game Industry

2019· article· en· W2947597695 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 institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCapitalismDemocratizationAutonomyStudioLeverage (statistics)SociologyVideo gameGame designPolitical scienceComputer scienceDemocracyPoliticsMultimediaLaw

Abstract

fetched live from OpenAlex

This article draws from ethnographic work in the game industry to challenge claims that digital platforms “democratize” cultural production by supporting small teams. I show how game developers exemplify the New Spirit of Capitalism in their search for creative autonomy outside of the risk-averse blockbuster console industry. Their risk of cultural production is ostensibly reduced by tools that leverage big data. By following one studio making free-to-play mobile games, I test the celebratory claims of democratization against the reality of implementing these now-essential analytics tools. The studio’s experiences demonstrate how mobile production for digital platforms intensifies game labor rather than facilitating its democratization in any straightforward way. It restricts creative autonomy, exacerbates the burden of risk on developers, and reinforces existing market and gender inequities. Rather than creatively liberating developers and expanding access to game development, data-driven design for digital platforms introduces new gatekeepers and literacies of exclusion.

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)0.001
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 score0.901
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.024
GPT teacher head0.297
Teacher spread0.273 · 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