Weighing In
Bibliographic record
Abstract
Neurodiversity as a concept, identity, and movement has radically challenged pre-existing ideas of human difference and value. First proposed by Judy Singer (1998) and largely developed through the work of community activists, neurodiversity posits an alternative to pathologizing and medicalized understandings of human differences. This article explores the ways neurodiversity is being used, defined, and deployed based on a corpus of 94 academic texts published across social science disciplines (2006–2021). Using discourse analysis methods derived primarily from Fairclough (2001, 2003), we examine how neurodiversity has been claimed and refashioned within academia. Neurodiversity was often seen as an embodied difference, and was variously portrayed as dichotomous, universal, or existing on a spectrum. Many authors followed an “Autism Plus” strategy, keeping autism at the center of discussions. Academic writers of the texts on neurodiversity overwhelmingly launched their own claims to authority, even as they simultaneously positioned themselves as out of the fray.
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 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".