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Record W2988456294 · doi:10.1111/jasp.12640

Comparing the apple of my eye: Parental reactions to academic social comparisons of their elementary school‐aged children

2019· article· en· W2988456294 on OpenAlexaffabout
Emily A. Vogels, W. Q. Elaine Perunovic

Bibliographic record

VenueJournal of Applied Social Psychology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPsychologyDevelopmental psychologyDomain (mathematical analysis)Social psychology

Abstract

fetched live from OpenAlex

Abstract The current study examines parents’ reactions to making social comparisons of their children on school‐related domains. Parents ( N = 117; ages 25 to 49; 94% women) of elementary school‐age children (ages 5 to 10; 57.3% girls) were recruited online from Facebook parenting groups and several school districts in Atlantic Canada. Participants were randomly assigned to make either an upward, a downward, or a lateral social comparison about their child’s ability in school. Participants reported the time since the event in comparison, their emotional reactions, their evaluations of their child’s ability in the domain, and how important they perceived the domain to be for their child’s future. Domain importance and evaluations of the child’s abilities also were measured prior to making the comparison. Significant differences based on social comparison condition were found for temporal distance, post‐comparison domain importance, and post‐comparison assessments of the child’s ability in the domain. The effect of social comparison on post‐comparison domain importance was not mediated by post‐comparison assessments of the child’s ability, suggesting a direct effect of comparisons on perceived domain importance. These findings suggest that the act of social comparison caused parents to reevaluate the importance of the domain of comparison and their child’s abilities in that domain. Implications for parents and educators are discussed.

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)0.001
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 score0.139
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.361
Teacher spread0.320 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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