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Record W2046203904 · doi:10.1348/026151008x390870

Children's reasoning about evaluative feedback

2009· article· en· W2046203904 on OpenAlexaff
Gail D. Heyman, Genyue Fu, Monica Sweet, Kang Lee

Bibliographic record

VenueBritish Journal of Developmental Psychology · 2009
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsPsychologyDevelopmental psychologyChinaFeedback regulationSocial psychology

Abstract

fetched live from OpenAlex

Children's reasoning about the willingness of peers to convey accurate positive and negative performance feedback to others was investigated among a total of 179 6- to 11-year-olds from the USA and China. In Study 1, which was conducted in the USA only, participants responded that peers would be more likely to provide positive feedback than negative feedback, and this tendency was strongest among the younger children. In Study 2, the expectation that peers would preferentially disclose positive feedback was replicated among children from the USA, and was also seen among younger but not older children from China. Participants in all groups took the relationship between communication partners into account when predicting whether peers would express evaluative feedback. Results of open-ended responses suggested cross-cultural differences, including a greater emphasis by Chinese children on the implications of evaluative feedback for future performance, and reference by some older Chinese children to the possibility that positive feedback might make the recipient 'too proud'.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.384
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), 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
Published2009
Admission routes1
Has abstractyes

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