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Record W3188742202 · doi:10.1080/15388220.2021.1952079

Association between Weight- and Appearance-related Bullying in High School and Postsecondary Academic Adaptation in Young Adults

2021· article· en· W3188742202 on OpenAlexafffund
Iris Fibia Stamate, Annie Aimé, Cynthia Gagnon, Aude Villatte

Bibliographic record

VenueJournal of School Violence · 2021
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversité du Québec en Outaouais
FundersFonds de Recherche du Québec-Société et Culture
KeywordsPsychologyPeer victimizationHuman factors and ergonomicsOverweightAssociation (psychology)Poison controlInjury preventionSuicide preventionOccupational safety and healthDevelopmental psychologyClinical psychologyAt-risk studentsMedicineObesityEnvironmental healthPedagogy

Abstract

fetched live from OpenAlex

This longitudinal study investigates the association between weight- and appearance-related bullying in high school and various dimensions of postsecondary school adaptation. The results showed that, in high school, weight-related bullying is more common than appearance-related bullying. Youth bullied because of weight were at higher risk of considering dropping out of college or university than peers who were bullied because of appearance. Those bullied because of overweight indicated being less academically involved than those bullied because of appearance. A cumulative effect of bullying sources was also observed, with a higher likelihood of youth bullied by two or more sources having considered dropping out and experiencing lower social integration and institutional commitment. These results highlight the need to consider weight-related bullying seriously and to intervene rapidly.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.370
Teacher spread0.339 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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