Autism-ness Does Not Exist, but Autism Does. Part 1: A Critic of the “Spectrum” Position Used to Describe, Diagnose, and Research Autism, and Its Alternative
Bibliographic record
Abstract
This article presents the historical roots of the dimensional perspective on autism, the epistemological and clinical critics of its assumptions and effects, and offers an alternative to it. Autism is increasingly being described as the "extreme far end" of a spectrum of traits distributed continuously and heterogeneously throughout the general population, and various comorbid neurodevelopmental conditions. This dimensional perspective, initially a response to the excesses of nominalism in the DSM, creates its own heuristic and clinical dead ends. In contrast with this dimensional paradigm, clinical experts recognize and diagnose prototypical autism based on the high similarity of specific clinical signs that are present during the preschool period. We propose viewing autism as a universal and evolutionarily stable, quasi-categorical possibility of human development, offering a prototypical presentation within a certain age range. We argue that prototypical autism needs to be further clinically described and scientifically investigated before anticipating the inclusion of nonprototypical presentations in an informative "autism spectrum." To achieve this, instruments based on qualitatively defined signs, with weighted diagnostic value, and universally associated with clinical certainty, must be developed. In the meantime, we recommend that all clinicians suspend the use of DSM-5 clinical specifiers to focus on clinical certainty and the application of differential diagnoses, rather than on the diagnostic thresholds of DSM-5 and of standardized instruments.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.067 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".