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Record W2170379815 · doi:10.1016/j.alter.2009.03.002

Occupation, poverty and mental health improvement in Ghana

2009· article· en· W2170379815 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAlter · 2009
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsMental illnessPovertyMental healthAsset (computer security)PsychologySocioeconomic statusEconomic shortagePsychiatryMedicineEconomic growthEconomicsEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

This study examines the relationship between a number of socioeconomic indicators (asset ownership, assets purchased, change in income, food shortage, kept job after illness) and two outcomes: improvement in mental illness and stability of mental illness. A sample of urban and rural Ghanaians reporting a mental illness (n = 400) was used. This focus on changes in mental illness differs from much previous work that examines mental illness status (i.e., whether or not a person has a mental illness). It was found that maintaining employment after the onset of illness was associated with both mental illness improvement and stability. Income increases were related to stability of mental illness only. Asset and food shortage measures were not found to be significant correlates of mental illness improvement or stability. This study indicates that measures taken to protect jobs and social status after the onset of mental illness symptoms are likely to facilitate improvements in mental health.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.317
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.400
Teacher spread0.368 · 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