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Record W4320501988 · doi:10.1051/shsconf/202315701022

The Effects of Poverty on Mental Health and Interventions

2023· article· en· W4320501988 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

VenueSHS Web of Conferences · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsPsychological interventionMental healthPovertyAnxietyMental illnessPsychiatryPsychologyDepression (economics)Clinical psychologyGovernment (linguistics)MedicinePolitical science

Abstract

fetched live from OpenAlex

It is well established that the link between mental illness and poverty is adverse. Consistent research has shown that individuals with low income have regularly been shown to be linked to an increased incidence of mental illness. Mental health is a significant part of one’s life because it can influence emotions, thoughts, and actions. The purpose of this research is to examine how poverty affects mental health and offer alternative interventions. Three mental illnesses—depression, anxiety, and posttraumatic stress disorder (PTSD) are reviewed in particular, and practical solutions from the perspectives of family, education, and public health are suggested. This research concludes that parenting is a major factor that causes depression and anxiety among children, poor parents with depressed or anxious symptoms also increase the risk of the mental disorder for their children. The poor relatively easier to encounter trauma and have a greater impact after trauma. Additionally, financial assistance from the government and competent policy is essential for providing effective interventions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.120

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 head0.335
Teacher spread0.303 · 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