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Record W2783136565 · doi:10.1192/s174936760000730x

Psychosocial and cultural motivations for self-inflicted burns among Iranian women

2005· article· en· W2783136565 on OpenAlexaff
Abdolaziz Rastegar Lari, Reza Alaghehbandan, Mohammad Taghi Joghataei

Bibliographic record

VenueInternational Psychiatry · 2005
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsNewfoundland and Labrador Centre for Applied Health Research
Fundersnot available
KeywordsPsychosocialAngerPsychiatryMental healthDistressPsychologySocial alienationSocial supportMedicinePublic healthClinical psychologySocial psychologyPolitical scienceAlienationNursing

Abstract

fetched live from OpenAlex

When the world of public health considers the health of women, one tendency is first and foremost to link the well-being of women to that of children and the family, and, legitimately, to the health of society overall. Epidemiological data point to sex differences in the patterns and clusters of psychiatric disorders and psychological distress. The origins of much of the pain and suffering particular to women can be traced to their social circumstances. Depression, hopelessness, exhaustion, anger and fear grow out of hunger, overwork, domestic and civil violence, entrapment and economic dependence. Understanding the sources of women's ill health demands awareness of how cultural and economic forces interact to undermine their social status. This article highlights aspects of social suffering among women in Iran. Self-inflicted burns, a significant indicator of mental health among Iranian women, are discussed in order to increase awareness of the phenomenon among the international community, as a first step towards initiating an improvement in the health of women in Iran.

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 score0.175
Threshold uncertainty score0.872

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)0.0010.000

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 head0.018
GPT teacher head0.346
Teacher spread0.328 · 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

Citations3
Published2005
Admission routes1
Has abstractyes

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