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Record W2980798514 · doi:10.1080/15283488.2019.1676245

My Animal Self: The Importance of Preserving Fantasy-Themed Identity Uniqueness

2019· article· en· W2980798514 on OpenAlexaff
Stephen Reysen, Courtney N. Plante, Sharon E. Roberts, Kathleen C. Gerbasi

Bibliographic record

VenueIdentity · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of WaterlooBishop's University
Fundersnot available
KeywordsFandomCopyingIdentity (music)FantasyPsychologyAngerSocial psychologyFeelingAestheticsSociologyMedia studiesArtLiterature

Abstract

fetched live from OpenAlex

Furries are fans of anthropomorphic art and media. A unique component of the fandom is the creation of individualized fursonas – anthropomorphic animal-themed identities to represent oneself. In the present research, we examined the effects of experiencing a threat to one’s fandom-themed fantasy identity (fursona) or to oneself. Furries read about another person copying (vs. not copying) one’s fursona (vs. public identity) prior to completing measures related to copycatting. In line with past research, when copied (vs. not), furries expressed anger, rated the situation as harmful and illegitimate, and viewed the other person unfavorably. Additionally, when copied, furries experienced more anger, perceived illegitimacy, and felt a greater threat to their freedom to display a unique identity when their fursona was copied than when their non-fan identity characteristics were copied. Together, the results point to the importance of furries’ fursonas to their sense of self.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.298
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2019
Admission routes1
Has abstractyes

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