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Record W2153095199 · doi:10.7870/cjcmh-2014-006

Mental Health and Poverty in Young Lives: Intersections and Directions

2014· article· en· W2153095199 on OpenAlexaffvenueabout
Kate Tilleczek, Moira Ferguson, Valerie Campbell, Katherine Elizabeth Lezeu

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsLaurentian UniversityUniversity of Prince Edward Island
Fundersnot available
KeywordsPovertyMental healthNegotiationStigma (botany)NarrativeSet (abstract data type)InequalitySociologyPsychologyGender studiesPolitical scienceSocial sciencePsychiatry

Abstract

fetched live from OpenAlex

This paper provides a conceptual synthesis of literature that addresses intersections of mental health, poverty, and school. It is based on a research synthesis for the youth policy framework for Ontario, Stepping Stones. The paper addresses research on challenges involving income inequality, poverty, and mental health that impinge upon school, and examines the enduring ill effects of these issues and academic struggles on young lives. It suggests practices that show promise to support youth. Findings suggest that transitions through school involve multiple developmental negotiations and are a critical site of slippages and successes. The paper ends with a set of reflective questions around age out (of the child and youth services system), the need to address stigma by animating the abundant character of young lives (addressing the subtleties and nuances of the life stories, biographies, and narratives of young people and their communities), the need for authentic collaborations across health and education, and working with and for young people as they collectively and individually determine and negotiate their lives.

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)0.012
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.009
Science and technology studies0.0180.031
Scholarly communication0.0210.027
Open science0.0020.016
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.345
Teacher spread0.313 · 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 designTheoretical or conceptual
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

Citations10
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Community Mental HealthSame topicYouth Education and Societal DynamicsFrench-language works237,207