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Record W2142764479 · doi:10.1353/mpq.2006.0037

How Children's Justifications of the "Best Thing to Do" in Peer Conflicts Relate to Their Emotional and Behavioral Problems in Early Elementary School

2006· article· en· W2142764479 on OpenAlexaff
Bonnie J. Leadbeater, Jeneva L. Ohan, Wendy L. G. Hoglund

Bibliographic record

VenueMerrill-Palmer Quarterly · 2006
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsPsychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

In this three-year longitudinal study, children were asked to choose the "best" strategy for dealing with hypothetical peer provocations and to justify "why" that was their choice at the end of first, second, and third grades. Teachers and parents also rated children's emotional and behavioral problems. Children's justifications were subjected to qualitative analyses to identify distinct content categories. These included getting others into trouble or avoiding it, dichotomous reasoning about good (kind) versus bad (mean) strategies, appeals to authorities for help, situation-specific solutions that anticipated consequences of actions, or general rules or solutions that could or should be used in similar conflicts to effect positive outcomes. These justification categories were related to the children's grade levels. Older children were more likely to use more story-specific justifications and to refer to the perspectives of others and to future consequences in their justification responses. Children who used justifications that involved getting others into trouble or avoiding it had higher levels of teacher ratings of concurrent emotional and behavioral problems at second and third grades and to parent ratings of emotional problems at third grade.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.285
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2006
Admission routes1
Has abstractyes

Explore more

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