Assessing social cognition: age-related changes in moral reasoning in childhood and adolescence
Bibliographic record
Abstract
OBJECTIVE: There is increasing recognition that socio-cognitive skills, such as moral reasoning (MR), are affected in a wide range of developmental and neuropsychological conditions. However, the lack of appropriate measures available to neuropsychologists poses a challenge for the direct assessment of these skills. This study sought to explore age-related changes in MR using an innovative visual tool and examine the developmental sensitivity of the task. METHOD: To address some of the methodological limitations of traditional measures of MR, a novel, visual task, the Socio-Moral Reasoning Aptitude Level (So-Moral), was used to evaluate MR in 216 healthy participants aged 6-20 years. RESULTS: The findings show a linear increase in MR from childhood to late adolescence with significant group differences between childhood (6-8 years) and preadolescence (9-11 years), and between early adolescence (12-14 years) and middle adolescence (15-17 years). CONCLUSIONS: Interpreted in light of current brain development research, the results highlight age-related changes in MR that offer insight into typical MR development and opportunities for comparisons with clinical populations. The findings also provide evidence of the potential of the So-Moral as a developmentally appropriate measure of MR throughout childhood and adolescence.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".