How is calendar calculation in autism possible? A language model.
Bibliographic record
Abstract
Detailed case studies of individuals with brain injuries have long provided valuable insights into how cognitive functions are organized. Similarly, the study of individuals with highly idiosyncratic cognitive abilities can shed light on the outer limits of human cognition. One such phenomenon is calendar calculation (CC), the ability to identify the day of the week that corresponds to a given date or the dates that match a particular calendar configuration. CC is the most commonly reported "special ability" in autism and is unique in its accuracy and speed, often surpassing experienced mathematicians. Recent findings suggest that a significant proportion of autistic children with oral language delays first acquire and prefer the written code, which may help pave the way for oral language acquisition. This atypical pathway for language acquisition invites a rethinking of the mechanisms underlying CC. In this article, we propose an integrative model in which the development and mastery of CC in autism are driven by the orientation of the innate linguistic cognitive resources toward an equivalent complex symbolic system. This model offers a novel perspective on the language trajectories observed in autism, their role in facilitating expertise in nonsocial complex material, and the broader flexibility of human language-based abilities. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.000 | 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 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".