MétaCan
Menu
Back to cohort
Record W2581069024 · doi:10.47741/17943108.110

Suicidio en las cárceles de Chile durante la década 2006-2015

2016· article· es· W2581069024 on OpenAlexaff
Francisco Ceballos-Espinoza, Ana‐María Chávez‐Hernández, Gustavo-Morelos Padilla-Gallegos, Antoon A. Leenaars

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2016
Typearticle
Languagees
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsWindsor Clinical Research
Fundersnot available
KeywordsHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

Chile apresenta um aumento alarmante de suicides, tanto na população geral quanto penitenciária, que preocupa à s autoridades da justiça e a saúde. Objetivo: analisar os suicídios consumados por prisioneiros em cadeias chilenas durante os anos 2006-2015, para obter o perfil de características sociais e criminó genas do ato suicida e dos centros penitenciários. Metodologia: de um total de 162 suicidos, 132 dos casos examinados pela Polícia das Pesquisas do Chile foram analisados. Resultados: 97.7% dos suicidos aconteceram nos homens de todas as idades (de 16 a 74 anos); duas terceiras partes (66.7%) aconteceram em pessoas com renda prévia à prisão, embora a maioria não tivesse os registros criminalis nem as sentenças precedentes (97.7%). Uma maioria (65.1%) aconteceu durante o primeiro ano da entrada. 73.5% eram solteiros, 47% só tinham estudos básicos, 84.8% não possuíam um ofício estável. Em 43.2% o estado depressivo foi relatado como ativador do suicido, e o método o mais comum foi o enforcamento (97%). As diferenças com estatísticas significativas de determinadas correlações foram encontradas, como entre o nível de estudos e a razão para o suicido, e entre o nível de estudos e renda prévia à prisão; também, uma correlação relevante que amostra que à idade menor, mais renda à prisão e menor nível de estudos

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueDialnet (Universidad de la Rioja)Same topicSuicide and Self-Harm StudiesFrench-language works237,207