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Record W1977029321 · doi:10.1080/14649365.2014.898781

Hacking the master code: cyborg stories and the boundaries of autism

2014· article· en· W1977029321 on OpenAlexaffabout
Victoria L. Henderson, Joyce Davidson, Katie Hemsworth, Sophie Edwards

Bibliographic record

VenueSocial & Cultural Geography · 2014
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsQueen's University
Fundersnot available
KeywordsAutismHumanitiesAutistic spectrumSociologyPsychologyArtDevelopmental psychology

Abstract

fetched live from OpenAlex

In this paper, we consider how the use of Internet technologies by individuals on the autism spectrum (AS) may contribute to recoding the spatial, sociopolitical, ontological, and epistemological boundaries commonly assumed to delimit autistic from non-autistic lifeworlds. Drawing on the work of Donna Haraway, we argue that the responses of AS individuals to a survey about online communication suggest these individuals are engaged in a form of cyborg writing, admixing constraints and opportunities in a way that opens alternative, polycentric, and indeterminate but nonetheless important political possibilities for people on (and off) the AS.

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0080.048
Scholarly communication0.0090.013
Open science0.0010.013
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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.

Study designQualitative
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

Citations11
Published2014
Admission routes2
Has abstractyes

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