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Record W2289948085 · doi:10.1177/1367877916636140

When passion isn’t enough: gender, affect and credibility in digital games design

2016· article· en· W2289948085 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Cultural Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAffect (linguistics)PassionCreativitySociologyProfessionalizationDiversity (politics)Identity (music)CredibilityGame studiesAestheticsGender studiesPublic relationsSocial psychologyPsychologyPolitical scienceMedia studiesSocial science

Abstract

fetched live from OpenAlex

Recent controversies around identity and diversity in digital games culture indicate the heightened affective terrain for participants within this creative industry. While work in digital games production has been characterized as a form of passionate, affective labour, this article examines its specificities as a constraining and enabling force. Affect, particularly passion, serves to render forms of game development oriented towards professionalization and support of the existing industry norms as credible and legitimate, while relegating other types of participation, including that by women and other marginalized creators, to subordinate positions within hierarchies of production. Using the example of a women-in-games initiative in Montreal as a case study, we indicate how linkages between affect and competencies, specifically creativity and technical abilities, perpetuate a long-standing delegitimization of women’s work in digital game design.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.101
GPT teacher head0.377
Teacher spread0.276 · 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