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Record W2127395773 · doi:10.1093/hsw/hlt013

Mental Health and Poverty in the Inner City

2013· article· en· W2127395773 on OpenAlexaff
Ujunwa Anakwenze, Daniyal Zuberi

Bibliographic record

VenueHealth & Social Work · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPovertyMental healthMental illnessUrbanizationCycle of povertySociologyPsychologyEconomic growthCriminologyPsychiatryEconomics

Abstract

fetched live from OpenAlex

Rapid urbanization globally threatens to increase the risk to mental health and requires a rethinking of the relationship between urban poverty and mental health. The aim of this article is to reveal the cyclic nature of this relationship: Concentrated urban poverty cultivates mental illness, while the resulting mental illness reinforces poverty. The authors used theories about social disorganization and crime to explore the mechanisms through which the urban environment can contribute to mental health problems. They present some data on crime, substance abuse, and social control to support their claim that mental illness reinforces poverty. The authors argue that, to interrupt this cycle and improve outcomes, social workers and policymakers must work together to implement a comprehensive mental health care system that emphasizes prevention, reaches young people, crosses traditional health care provision boundaries, and involves the entire community to break this cycle and improve the outcomes of those living in urban poverty.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.064
GPT teacher head0.430
Teacher spread0.366 · 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

Citations120
Published2013
Admission routes1
Has abstractyes

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