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Record W1965071028 · doi:10.3402/ijch.v61i2.17443

Violence, sexual abuse and health in Greenland

2002· article· en· W1965071028 on OpenAlexaboutno aff
Tine Curtis, Finn Breinholt Larsen, Karin Helweg‐Larsen, Peter Bjerregaard

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2002
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsSexual abuseSexual violencePopulationPsychiatryDomestic violencePoison controlMedicineSuicide preventionInjury preventionOccupational safety and healthMental healthReproductive healthClinical psychologyPsychologyMedical emergencyEnvironmental health

Abstract

fetched live from OpenAlex

The purposes of the study were to analyse the lifetime prevalence of violence and sexual abuse among the Inuit in Greenland and to study the associations between health and having been the victim of violence or sexual abuse. Associations were studied with specific attention to possible differences between women and men. Further, response rates were analysed specifically in order to understand consequences of including questions on violence and sexual abuse in the questionnaire survey. The analyses were based on material from a cross-sectional health interview survey conducted during 1993-94 with participation from a random sample of the Inuit population in Greenland (N = 1393). The prevalence of ever having been a victim of violence was 47% among women and 48% among men. Women had more often than men been sexually abused (25% and 6%) (p < 0,001) and had more often been sexually abused in childhood (8% and 3%) (p = 0.001). Having been the victim of violence or sexual abuse was significantly associated with a number of health problems: chronic disease, recent illness, poor self-rated health, and mental health problems. The associations between having been the victim of violence or sexual abuse and health was stronger for women than for men. It is possible to secure a reasonably high response rate in a general health survey that includes questions on violence and sexual 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.577

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)0.0010.000

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 head0.048
GPT teacher head0.358
Teacher spread0.310 · 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

Citations73
Published2002
Admission routes1
Has abstractyes

Explore more

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