Locally oriented perception with intact global processing among adolescents with high‐functioning autism: evidence from multiple paradigms
Bibliographic record
Abstract
BACKGROUND: According to predictions from the Weak Central Coherence (WCC) theory for perceptual processing, persons with autism should display a tendency to focus on minute details rather than on a more general picture (Frith & Happé, 1994). However, the evidence for this theory is not consistent with findings of an enhanced detection of local targets (Plaisted, O'Riordan, & Baron-Cohen, 1998b; Plaisted, Swettenham, & Rees, 1999), but a typical global bias (Mottron, Burack, Stauder, & Robaey, 1999; Ozonoff, Strayer, McMahon, & Filloux, 1994). METHOD: Adolescents with high-functioning autism and CA- (approximately 15 years) and IQ- (approximately 105-110) matched typically developing adolescents were administered a series of global-local visual tasks, including a traditional task of hierarchical processing, three tasks of configural processing, and a disembedding task that involved rapid perceptual processing. RESULTS: No group differences were found on either the traditional task of hierarchical processing or on tasks of configural processing. However, group differences were found on the disembedding task as the search for embedded, in relation to isolated stimuli, was slower for the typically developing adolescents but similar for the participants with autism. CONCLUSIONS: These findings are consistent with other reports of superior performance in detecting embedded figures (Jolliffe & Baron-Cohen, 1997; Shah & Frith, 1983), but typical performance in global and configural processing (Mottron, Burack et al., 1999; Ozonoff et al., 1994) among persons with high-functioning autism. Thus, the notions of local bias and global impairment that are part of WCC may need to be reexamined.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".