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Record W2939535744 · doi:10.4236/psych.2019.105042

Street Children: Implication on Mental Health and the Future of West Africa

2019· article· en· W2939535744 on OpenAlexaboutno aff
Davou Francis John, Armiya’u Aishatu Yusha’u, Tungchama Friday Philip, Maigari Yusufu Taru

Bibliographic record

VenuePsychology · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyQuarter (Canadian coin)Mental healthPsychologyDevelopmental psychologyPsychiatryClinical psychologyGeographyEconomic growth

Abstract

fetched live from OpenAlex

Background: Street life is a common sight among children in Africa including Nigeria. Distressed, hungry and poorly groomed children can be seen roaming the streets in search for means of survival from well-wishers and passersby. Poverty, cultural practices and religious belief have been cited as being responsible for such problems. The study aimed at determining the sociodemographic factors responsible for children being on the streets. It also seeks to establish the mental health effects of children being on the streets. Two questionnaires were designed by the researchers to collect information about respondents. One hundred and seven (107) of these children were interviewed. The study revealed the predominance of male children (91.6%), children from Islamic background (85.0%) whose parents were involved in unskilled jobs (72.0%). A statistically significant relationship was observed between street life and sociodemographic factors. Over four-fifth of the children have faced various forms of physical, sexual, emotional abuse with about three-quarter involved with alcohol and other drugs. In conclusion, the study revealed that poverty, low family income and large family sizes were responsible for children being on the streets.

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 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 score0.194
Threshold uncertainty score0.181

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 head0.026
GPT teacher head0.429
Teacher spread0.402 · 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 teacher head, 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

Citations10
Published2019
Admission routes1
Has abstractyes

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