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Record W2029764772 · doi:10.1080/13811110600582406

The Balkan Piedmont: Male Suicide Rates Pre-war, Wartime, and Post-war in Serbia and Montenegro

2006· article· en· W2029764772 on OpenAlexaff
S. Selakovic-Bursic, Elisabeth Haramic, Antoon A. Leenaars

Bibliographic record

VenueArchives of Suicide Research · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsVeterans Affairs Canada
Fundersnot available
KeywordsMontenegroSpanish Civil WarDemographySuicide preventionEpidemiologyPoison controlSuicide ratesSuicide methodsMedicineGeographyHistoryAncient historyEnvironmental healthSociologyArchaeology

Abstract

fetched live from OpenAlex

The epidemiology of suicide in Serbia and Montenegro from 1989 to 2003, a period of civil war, is presented. Following the break-up of former Yugoslavia, Serbia and Montenegro underwent a period of war from 1991-1994 and another in 1999. During the war years, the number of suicides increased, reaching its peak in 1993. Male suicides outnumbered female suicides by a ratio of 2:1. Male suicides decreased slightly after the war of 1991-1994 only to rise in 1997 and continue at this higher level throughout the nineties. In Serbia alone, male suicide reached its peak in 2002 (nearly 29/100,000). The methods of suicide changed significantly, with the use of firearms doubling during and after the war years. Speculations are offered about the findings, many consistent with Durkheim's classical hypothesis concerning suicide and unpopular wars.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.083
GPT teacher head0.454
Teacher spread0.372 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2006
Admission routes1
Has abstractyes

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