The use of the macCAT-CA with adolescents: An item response theory investigation of age-related measurement bias.
Bibliographic record
Abstract
Despite the application of the MacCAT-CA to juveniles, questions been raised regarding the appropriateness of this tool for adolescents. The current study tested for age-related measurement bias using data from the MacArthur Juvenile Adjudicative Competence Study (n = 1393). Five of the MacCAT-CA items showed age-related measurement bias (i.e., DIF) for adolescents aged 11-15, and three items showed DIF for adolescents aged 16-17. Several items (e.g., understanding of juries) were more difficult for adolescents than adults matched at the same latent level of capacity, suggesting that these items might underestimate adolescents' legal capacities. Contrary to expectations, there was little evidence of age-related measurement bias on the Appreciation scale. The use of the MacCAT-CA in research and clinical settings is discussed.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".