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Record W7017721856

Características del comportamiento suicida en cárceles de Colombia.

2014· article· en· W7017721856 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Skills and Education
Canadian institutionsnot available
Fundersnot available
KeywordsIntrapersonal communicationPrisonContext (archaeology)Quarter (Canadian coin)Interpersonal communicationSuicide preventionTest (biology)
DOInot available

Abstract

fetched live from OpenAlex

Objective. This study of a descriptive correlational type was aimed at establishing which of the incarceration context variables of time, method and place appear more frequently in 60 inmates involved in situations dealing with suicidal thoughts, suicide attempts and completed suicide during the first quarter of 2013 in the prisons and correctional institutions attached to the INPEC, the National Penitentiary and Prison Institute of Colombia. Method. The intentional sample consisted of 60 inmates, 68.3 % of which were men and 31.7 %\nwere women with an average age of 28.02 years and a standard deviation of 8.03 years. Results. Through a format for the exclusive use by the INPEC and the "Statisticals Package for the Social Sciences" (SPSS) software, the result obtained was that suicide attempt, with 76.7 %, is the most frequently occurring conduct. Likewise, through the Pearson Chi-squared test (X2), the existence of statistically significant relations between the suicidal behavior type and gender and method used was established, instead of event and type of suicidal\nconduct. Conclusions. The initial incarceration stage is the most risky period (one to five months) in the emergence of the first suicidal attempt (41.7 %), which may be explained as triggered by the affective and emotional maladjustment fragmenting the daily life of inmates in their interpersonal and intrapersonal relations, where positive communication is absent and both moral and psychological stress are revealed (OMS, 2000).

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 score0.427
Threshold uncertainty score0.979

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.296
Teacher spread0.286 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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