MétaCan
Menu
Back to cohort
Record W4387668442 · doi:10.1080/01639625.2023.2268253

Weaponized Autism: Making Sense of Violent Internalized Ableism in Online Incel Communities

2023· article· en· W4387668442 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

VenueDeviant Behavior · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsAbleismAutismHegemonic masculinityMasculinityPsychologyPopulationSocial psychologyIdentity (music)SociologyGender studiesDevelopmental psychologyPsychoanalysisAesthetics

Abstract

fetched live from OpenAlex

Much attention has been paid to incel communities in recent years. Comprised of involuntary celibate individuals who are dissatisfied with their shared experiences of romantic and sexual rejection, incels blame women and the societal rejection of hegemonic masculinity as the cause of their grievances. Current scholarship has produced conflicting results regarding the prevalence of autism within incel communities when compared to the general population. At the same time, no research to date has explored the intersection of incels and autism using perspectives from individuals in the incel community. Using a critical autism lens, this present study thematically analyzes 20 online incel message boards to explore the sense-making of self-identified autistic incels. Findings indicate that incels’ internalized ableism of autism is employed to categorically justify the victimhood and entitlement that grounds their ideology. This weaponization of autism is then used to promote ableism and networked misogyny. Implications for understanding ableist and misogynistic beliefs associated with inceldom are provided.

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)0.001
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 score0.333
Threshold uncertainty score0.998

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 science0.0000.000
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 head0.096
GPT teacher head0.386
Teacher spread0.290 · 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