Affective intensities and autistic misfitting: on surviving violence at school
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.
Bibliographic record
Abstract
This paper analyses 19 autistic individuals’ stories of school experiences in Canada drawn from the Re•Storying Autism project, which aims to challenge dominant deficit logics of autism and re-story ways of becoming and belonging in schools. In our analysis, we were struck by ubiquitous stories of relentless, dehumanizing violence and by occasional moments of belonging and care. Through the feminist materialist ontology and metaphor of (mis)fitting and feminist affect theory, we engage discursive, material, and affective dimensions of autistic school experiences of violence and belonging to challenge harmful deficit logics circulating therein and open avenues for understanding affects/effects alongside pathways for transformation. We argue that misfitting and violence in schools materializes through assemblages produced, in part, via a constellation of affects – fear, hatred, discomfort – accompanying ableist developmentalist legacies still structuring formal education systems. Our approach intervenes into feminist neomaterialist and critical autism studies, which have yet to grapple with autism and school violence. Based on this analysis combined with stories of relational and creative responses to misfitting, we consider opportunities for transgression and advocacy that can expand possibilities for affirming (neuro)diverse becomings and for remaking school practices and spaces in more relational, contextual, and ethical ways.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it