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Record W4311872840 · doi:10.32920/21691820

Cosplay: Imaginative self and performing identity

2022· preprint· en· W4311872840 on OpenAlexaff
Osmud Rahman, Wing‐sun Liu, Brittany Hei-man Cheung

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEthnographySubculture (biology)Identity (music)NegotiationHEROGratificationSociologyPsychologyAestheticsGender studiesSocial psychologyMedia studiesArtAnthropologySocial scienceLiterature

Abstract

fetched live from OpenAlex

<p>This study examines the emerging cosplay subculture in Hong Kong. A quasi-ethnographic approach including participation, observation, photography, and in-depth interviews was employed to understand the underlying motives and experiences of those engaged in cosplay activities. Authenticity, affective attachment, the extended self, and the negotiation of boundaries are also discussed in this article. From this study, it is evident that cosplay can give participants pleasurable experiences, meaningful memories, self-gratification, and personal fulfillment. Through this participatory activity, cosplayers can momentarily escape from reality and enter into their imaginative world. It is a form of role/identity-transformation from an “ordinary person” to a “super hero,” from a “game player” to a “performer,” and from “adulthood” to “childhood.”</p>

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.339
Teacher spread0.320 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2022
Admission routes1
Has abstractyes

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