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Record W1851258138 · doi:10.1080/1369118x.2012.756048

MAKING A NAME IN GAMES

2013· article· en· W1851258138 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

VenueInformation Communication & Society · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIncubatorStatus quoIndie filmValue (mathematics)Power (physics)EntrepreneurshipPublic relationsSociologyBusinessPolitical scienceComputer scienceMedia studies

Abstract

fetched live from OpenAlex

This article explores the development and implementation of a Toronto-based incubator supporting local women in developing their own games. The incubator was created to help change the current (male-dominated) status quo of game production, promising participants skills sharing, support for the development of a new game, and entry into the local community of indie games developers. It was at the same time part of a large network of commercial and non-commercial interests with a shared agenda of promoting the local digital innovation scene. These different motivations and actors are considered to understand the nature of this complex social network market and the circulation of particularly feminized affective labour therein, detailing how value, reward, and benefit are conceptualized throughout this network. The article focuses on how and where these understandings are in alignment and where they fall apart, revealing problematic structures of power and control linked in particular to gender and entrepreneurialism in the area of digital innovation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.006
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.030
GPT teacher head0.260
Teacher spread0.230 · 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