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Record W2556589803

A Gender-Based Comparison of Levels and Determinants of Adolescent Well-Being: Results from a Canadian National Survey

2010· article· en· W2556589803 on OpenAlexaffabout
Robert D. Weaver, Nazim Habibov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAggressionWell-beingPsychologyNational Longitudinal SurveysPovertySelf-esteemDevelopmental psychologyDemographyDepression (economics)Clinical psychology
DOInot available

Abstract

fetched live from OpenAlex

Using data from Canada’s National Longitudinal Survey of Children and Youth, the authors compared the levels of well-being between female and male adolescents and examined the specific determinants of well-being for each gender. The authors determined that a higher proportion of female youth reported doing well in school whereas the male youth reported higher levels of self-esteem and physical aggression. For both genders, the number of children living in the home and level of parental education were associated with their school performance. The self-esteem of female youth was apparently influenced by various parental factors such as home ownership status, level of education, and depression, whereas family dysfunction was associated with the self-esteem of male youth. Living in poverty, family dysfunction and parental age were all associated with the physical aggression levels of male youth, while for females, physical aggression was seemingly influenced by the level of parental education.

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 score0.047
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.116
GPT teacher head0.383
Teacher spread0.267 · 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

Citations2
Published2010
Admission routes2
Has abstractyes

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