MétaCan
Menu
Back to cohort
Record W3145140659 · doi:10.1177/1469540521993928

Speculating on Steam: Consumption in the gamblified platform ecosystem

2021· article· en· W3145140659 on OpenAlex
Andrei Zanescu, Marc J. Lajeunesse, Martin French

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

VenueJournal of Consumer Culture · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConsumption (sociology)Order (exchange)Business modelPoliticsDistribution (mathematics)Sharing economyBusinessGame theoryMarketingEconomicsIndustrial organizationSociologyComputer sciencePolitical scienceMicroeconomicsSocial science

Abstract

fetched live from OpenAlex

The rise of platforms as the premier model of videogame distribution has led to a number of changes in the business models of producers and distributors. Consumers are constantly hailed by games platforms through freemium business models that offer cosmetic items contained in loot boxes or recurring subscriptions. Thus far, game studies and consumer studies have been unable to account for the totality of how these new and dynamic platforms circumvent legal barriers and attract potential consumers. This paper argues that a hybrid research model combining platform studies, socio-cultural critique of gamblification, and political economy is required in order to theorize and explicate how these platforms operate. The platformized and gamblified model for game distribution seeks to regulate and configure networks of association between consumers and producers with the ultimate aim of eliciting participation on platforms.

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 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 score0.886
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.057
GPT teacher head0.329
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