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Parenting practices during middle adolescence and high school dropout

2019· article· en· W2970456577 on OpenAlexafffund
Kamel Afia, Éric Dion, Véronique Dupéré, Isabelle Archambault, Jessica R. Toste

Bibliographic record

VenueJournal of Adolescence · 2019
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
FundersFonds de Recherche du Québec - SantéSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsPsychologyDropout (neural networks)NeglectDevelopmental psychologyImmigrationSchool dropoutClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Despite inconclusive findings, educational researchers have long considered adequate parenting practices instrumental in preventing high school dropout among adolescents. The present short-term retrospective study focuses on parenting practices during middle adolescence when dropout typically occurs. METHODS: = 16.0 years) from low-income neighborhoods included very recent dropouts and matched still-in-school students. A global score reflecting the quality of parenting practices during the period preceding dropout (or comparable period) was derived from adolescents' answers to a well-established structured interview protocol. Transcripts of interviews were also used to identify the potentially disruptive challenges (e.g., parental incarceration) that families faced. RESULTS: Results show a robust relationship between current parenting practices and dropout that was not moderated by challenging family circumstances or immigration history. Descriptive findings indicate that extreme and relatively rare cases of parental neglect were associated with a high dropout risk, but that most dropouts lived in families where communication and supervision, although not entirely absent, were minimal. CONCLUSION: Offering systematic support to parents of middle adolescents could help to prevent dropout in high-risk communities.

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)0.004
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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 head0.023
GPT teacher head0.283
Teacher spread0.260 · 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

Citations21
Published2019
Admission routes2
Has abstractyes

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