The Children’s Social Understanding Scale: Construction and validation of a parent-report measure for assessing individual differences in children’s theories of mind.
Bibliographic record
Abstract
Children's theory of mind (ToM) is typically measured with laboratory assessments of performance. Although these measures have generated a wealth of informative data concerning developmental progressions in ToM, they may be less useful as the sole source of information about individual differences in ToM and their relation to other facets of development. In the current research, we aimed to expand the repertoire of methods available for measuring ToM by developing and validating a parent-report ToM measure: the Children's Social Understanding Scale (CSUS). We present 3 studies assessing the psychometric properties of the CSUS. Study 1 describes item analysis, internal consistency, test-retest reliability, and relation of the scale to children's performance on laboratory ToM tasks. Study 2 presents cross-validation data for the scale in a different sample of preschool children with a different set of ToM tasks. Study 3 presents further validation data for the scale with a slightly older age group and a more advanced ToM task, while controlling for several other relevant cognitive abilities. The findings indicate that the CSUS is a reliable and valid measure of individual differences in children's ToM that may be of great value as a complement to standard ToM tasks in many different research contexts. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
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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 | 0.006 | 0.019 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".