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Record W2089652848 · doi:10.1177/001698620204600103

Gifts and Talents as Sources of Envy in High School Settings

2002· article· en· W2089652848 on OpenAlexaffabout
Line Massé, Franfoys Gagné

Bibliographic record

VenueGifted Child Quarterly · 2002
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsUniversité du QuébecUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPsychologyPerspective (graphical)Social psychologySocial comparison theoryMathematics education

Abstract

fetched live from OpenAlex

This article explores a new empirical approach to explaining some social difficulties experienced by talented students: peer envy toward their gifts and talents. A sample of 689 French Canadian high school students completed two questionnaires addressing both the envy they felt anid the envy expressed toward them. The results focus on two themes: (a) the relative intensity and frequency of envy toward gifts and talents as compared to other potential objects of envy, and (b) the influence of various student characteristics or school settings on the students' answers. The results show a large discrepancy between the envious and envied perspectives. In the first perspective, students did manifest more envy toward their peers' social and financial successes than toward their academic achievements or intelligence. On the other hand, when invited to identify, objects for which they were envied, academic talent became the object most frequently reported.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.099
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0060.008
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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

Citations31
Published2002
Admission routes2
Has abstractyes

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