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Record W4230864085 · doi:10.31234/osf.io/8xvzr

“My Group Is Discriminated against, but I’m Not”: Denial of Personal Discrimination in Furry, Brony, Anime, and General Interest Fan Groups

2018· preprint· en· W4230864085 on OpenAlexaff
Connor Emont Leshner, Stephen Reysen, Courtney N. Plante, Daniel Chadborn, Sharon E. Roberts, Kathleen C. Gerbasi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsMacEwan University
Fundersnot available
KeywordsAnimeDenialFandomPsychologySocial psychologyGroup (periodic table)SociologyMedia studiesPsychoanalysis

Abstract

fetched live from OpenAlex

The authors examined perceived discrimination directed toward one’s fan group and toward oneself in multiple groups of fans. Specifically, furries, bronies, anime fans, and a group of miscellaneous fans completed measures assessing the extent to which they perceived discrimination toward both their fan group and toward themselves. Across all samples, participants reported greater discrimination directed toward their fan group than toward themselves, suggesting denial of personal discrimination. The difference between personal discrimination and fandom discrimination is a reliable one, as suggested by its persistence despite considerable differences between the groups with regard to the level of societal stigma. The implications of these results and future directions for this line of research 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.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.321
Teacher spread0.271 · 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 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

Citations3
Published2018
Admission routes1
Has abstractyes

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Same topicAsian Culture and Media StudiesFrench-language works237,207