MétaCan
Menu
Back to cohort
Record W2140039219 · doi:10.1177/1469540513493209

Playing by the market rules: Promotional priorities and commercialization in children’s virtual worlds

2013· article· en· W2140039219 on OpenAlexaff
Sara M. Grimes

Bibliographic record

VenueJournal of Consumer Culture · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCommercializationMetaverseEntertainmentVirtual economyPromotion (chess)AdvertisingClubDatabase transactionMarketingPublic relationsSociologyWork (physics)BusinessPolitical scienceVirtual realityLawComputer scienceEngineeringPoliticsWorld Wide Web

Abstract

fetched live from OpenAlex

This paper explores the emerging relationship between commercial priorities and technological design within children's virtual worlds, through a comparative case study analysis of the promotional contents and marketing features found within six commercial, game-themed virtual worlds targeted specifically to children under the age of 13: Disney's Club Penguin and Toontown, Mattel's BarbieGirls, Cookie Jar's Magi-Nation, Nickelodeon's Nicktropolis, and Corus Entertainment's GalaXseeds. Focusing on key trends identified across all six cases, the paper argues that these games are designed to mobilize virtual economies for real money transaction and self-promotion, utilizing game mechanics, virtual items, and other features for various forms of branding and third-party advertising strategies. A critical analysis of these trends and other relevant findings is provided, through a consideration of how such processes work to mobilize players' affective labor, while concurrently limiting potentially important opportunities for participation, communication, access, and cultural rights, such as freedom of speech.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.206

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 communication0.0000.001
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Consumer CultureSame topicDigital Games and MediaFrench-language works237,207