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Record W4200365168 · doi:10.3389/fpsyg.2021.695258

One Ring Fit to Rule Them All? An Analysis of Avatar Bodies and Customization in Exergames

2021· article· en· W4200365168 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.

Bibliographic record

VenueFrontiers in Psychology · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsCarleton University
Fundersnot available
KeywordsAvatarPersonalizationPopularityPsychologyPriming (agriculture)Human–computer interactionIdentification (biology)Social psychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

With the growing popularity of exergames, researchers have noted the importance of presenting players with customizable avatars to encourage the long-term adoption of healthy behaviors offline. However, the "idealized" avatar bodies presented in avatar customization interfaces can represent limited body types and often problematically represent gender as binary. In this paper, we present a systematic analysis of the avatar customization interfaces of six console-based exergames. Results of our analysis indicate that customization options tend to be limited in exergames, especially with regard to body type and gender. Implications for avatar self-priming, self-identification, and healthy behavior adoption are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.531

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 communication0.0000.000
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 head0.075
GPT teacher head0.333
Teacher spread0.257 · 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