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Record W2892393971 · doi:10.1017/dmp.2019.16

Emotional and Physical Child Abuse in The Context of Natural Disasters: A Focus on Haiti

2019· article· en· W2892393971 on OpenAlexaff
Sony Subedi, Susan A. Bartels, Colleen Davison

Bibliographic record

VenueDisaster Medicine and Public Health Preparedness · 2019
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsQueen's University
Fundersnot available
KeywordsContext (archaeology)Poison controlPsychological abusePhysical abusePsychological interventionInjury preventionSuicide preventionOccupational safety and healthNatural disasterGeographyEnvironmental healthChild abusePsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the social and living conditions of households in Haiti before and after the 2010 earthquake and to determine the prevalence of emotional and physical abuse of children aged 2 to 14 in households after the earthquake. METHODS: Nationally representative samples of Haitian households from the 2005/2006 and 2012 phases of the Demographic and Health Surveys were used. Descriptive data were summarized with frequencies and measures of central tendency. Chi-squared and independent t tests were used to compare pre-earthquake and post-earthquake data. Basic mapping was used to explore patterns of child abuse in relation to proximity to the epicenter. RESULTS: Comparison of pre-earthquake and post-earthquake data showed noteworthy improvements in the education attainment of the household head and possession of mobile phones after the earthquake. The prevalence of emotional, physical, and severe physical abuse in 2012 was estimated to be 78.5%, 77.0%, and 15.4%, respectively. Mapping revealed no conclusive patterns between the proximity of each region to the epicenter and the prevalence of the different forms of abuse. However, the prevalence of severe physical abuse was notably higher in settlement camps (25.0%) than it was in Haiti overall (15.4%). CONCLUSIONS: The high prevalence of child abuse in Haiti highlights an urgent need for interventions aimed at reducing occurrences of household child abuse.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.340
Teacher spread0.302 · 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 designQualitative
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

Citations14
Published2019
Admission routes1
Has abstractyes

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