Orotating parafundities: reading Hopkins, Dickinson, Murray, and Carson autistically
Bibliographic record
Abstract
Autistic people use and understand language differently than do non-autistic people; this principle is chief among diagnostic criteria for autism spectrum disorder (ASD), and yet little attention has been paid to this phenomenon as it pertains to autistic engagement with literature. This thesis examines the generative potential of what I have termed “autistic close reading” to unlock new interpretations of work by four poets whose writing has been considered unusual, impenetrable, perplexing, and weird: Emily Dickinson (1830-1886), Gerard Manley Hopkins (1844-1889), Les Murray (1938-2019), and Anne Carson (1950-). Accepting the premise that autistic reading experiences are, like many autistic experiences, “particular and peculiar,” I look at how autistic cognitive style, sensory responsiveness, communication differences, and social alterity work to create unique relationships between autistic readers and the literary material we enjoy. Engaging a taxonomy of autistic language usage developed by theorist Julia Miele Rodas, I examine the distinct overlap between autistic expression and formal poetic technique, and I explore potential implications of this overlap in terms of language use and language reception by autistic people. Drawing on work by Jack Halberstam, M. Remi Yergeau, Ralph John Savarese, and Nick Walker, this thesis takes a neuroqueer and neurocosmopolitan approach to Hopkins, Dickinson, Murray, and Carson as cultural figures, and proposes new contexts to elucidate their poems and projects. The dissertation is bracketed by first-person commentary on my own relationship to language as an autistic poet, and on my experiences as an autistic researcher. As my title indicates, this thesis is as much about the act of reading while autistic as it is about the critical assertions engendered by such an act.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".