CAT-Q MSCS BASC2 Pre-Print
Bibliographic record
Abstract
Background: Camouflaging, defined as the use of strategies to compensate for or hide autistic traits, is associated with internalizing behaviour (i.e., anxiety and depression) in both autistic and non-autistic people. Non-autistic adults who have poorer social competence tend to engage in more camouflaging, thus it’s unclear whether the increase in internalizing behaviour associated with camouflaging may be explained by poor social competence, rather than camouflaging itself. The purpose of this study was to extend previous research on camouflaging and internalizing behaviour among non-autistic people through examination of the role of social competence. Methods: In this study, 315 non-autistic young adults completed the Multidimensional Social Competence Scale (MSCS) to assess their social competence, the Camouflaging of Autistic Traits Questionnaire (CAT-Q) to assess their use of camouflaging strategies, and the Behaviour Assessment Scale for Children 2 – Self-Report of Personality, College Version (BASC-2 SRP-COL) to assess their internalizing behaviour. Results: We found that camouflaging predicted internalizing behaviour among non-autistic young adults after controlling for social competence, autistic traits, age, IQ, and gender. Camouflaging partially mediated the relationship between social competence and internalizing behaviours. Conclusions: These results suggest that the use of camouflaging strategies is uniquely associated with internalizing behaviour over and above social competence and may, in part, contribute to the increased internalizing behaviours observed in individuals with poorer social competence.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.944 | 0.898 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".