Making Sense of Divergent Interpretations of Conflict and Developing an Interpretive Understanding of Mind
Bibliographic record
Abstract
Our goals in this study were to develop a measure of children's understanding of divergent interpretations of conflict and relate that measure to children's more general interpretive understanding of mind (Carpendale & Chandler, 1996). Eighty-nine children between 4 and 9 years of age heard 4 conflict stories in which fault was ambiguous. Children overwhelmingly suggested that antagonists would blame each other and adequately justified those judgments. However, children under 7 years did not believe that it made sense for antagonists to disagree, and children were better able to explain why mutual blame made sense as they grew older. Children's judgments of the legitimacy of and explanations for divergent conflict interpretations were correlated with similar measures assessing their understanding of the general interpretive quality of mind. Findings are discussed in terms of the role of everyday interaction for the gradual acquisition of interpretive understanding.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".