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Record W4297830730 · doi:10.1007/s10803-022-05701-0

Understanding the Use of the Term “Weaponized Autism” in An Alt-Right Social Media Platform

2022· article· en· W4297830730 on OpenAlexaff
Christie Welch, Lili Senman, Rachel Loftin, Christian Picciolini, John Elder Robison, Alexander Westphal, Barbara Perry, Jenny Nguyen, Patrick Jachyra, Suzanne Stevenson, Jai Aggarwal, Sachindri Wijekoon, Simon Baron‐Cohen, Melanie Penner

Bibliographic record

VenueJournal of Autism and Developmental Disorders · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsOntario Tech UniversityHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
Fundersnot available
KeywordsAutismTerm (time)PsychologySocial mediaDevelopmental psychologyPolitical scienceLawPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: The term "weaponized autism" is frequently used on extremist platforms. To better understand this, we conducted a discourse analysis of posts on Gab, an alt-right social media platform. METHODS: We analyzed 711 posts spanning 2018-2019 and filtered for variations on the term "weaponized autism". RESULTS: This term is used mainly by non-autistic Gab users. It refers to exploitation of perceived talents and vulnerabilities of "Weaponized autists", described as all-powerful masters-of-technology who are devoid of social skills. CONCLUSIONS: The term "weaponized autism" is simultaneously glorified and derogatory. For some autistic people, the partial acceptance offered within this community may be preferable to lack of acceptance offered in society, which speaks to improving societal acceptance as a prevention effort.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.129
GPT teacher head0.294
Teacher spread0.164 · 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.

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

Citations8
Published2022
Admission routes1
Has abstractyes

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