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Record W2100050278 · doi:10.1177/0022022109354640

Suicide in Different Cultures: A Thematic Comparison of Suicide Notes From Turkey and the United States

2010· article· en· W2100050278 on OpenAlexaff
Antoon A. Leenaars, Aslıhan Sayin, Selçuk Candansayar, Lindsey Leenaars, Taner Akar, Birol Demirel

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSuicidologyCollectivismIndividualismTurkishSuicide preventionCross-cultural studiesPsychologyThematic analysisCross-culturalSuicide attemptCultural diversitySocial psychologyPoison controlHuman factors and ergonomicsSociologyMedicinePolitical scienceSocial scienceQualitative researchEnvironmental healthLawAnthropology

Abstract

fetched live from OpenAlex

Suicide is a global concern, hence, cross-cultural research ought to be central; yet, there is a paucity of cross-cultural study in suicidology. A thematic or theoretical-conceptual analysis of 60 suicide notes drawn from Turkey and the United States, matched for age and sex, was undertaken, based on Leenaars’s empirical-based multidimensional model of suicide. The results suggested that there were more culturally common factors than specific differences; yet, not consistent with previous cross-cultural studies of suicide notes, differences emerged in Turkey notes expressing more indirect and veiled communications (indirect expressions). Specifically, Turkish notes expressed that there may be more reasons to the act than the person writes. It was concluded that the model may be applicable to suicide in both countries, but also much greater cross-cultural study is warranted on specific cultural risk factors. A question raised is whether the findings are related to collectivism versus individualism.

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)0.001
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 score0.076
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.067
GPT teacher head0.453
Teacher spread0.387 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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