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Record W2936899138 · doi:10.47741/17943108.32

Responsabilidad Penal Adolescente en Chile: Propuestas para implementar la intervención psicosocial en Secciones Juveniles

2018· article· en· W2936899138 on OpenAlexaboutno aff
Daniela Avello-Sáez, Alba Zambrano Constanzo, Alberto Román Morales

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Issues and Policies in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesSociologyArt

Abstract

fetched live from OpenAlex

Abstract This study aims to analyze the design and management characteristics of psychosocial intervention projects which are conducted by executing entities in juvenile sections of prisons in the Southern Chile, stating mechanisms to improve the intervention developed with young lawbreakers starting from the experience of the programs participating teams. 32 professionals of four teams took part in this study. Data production, group interviews and documents review techniques were implemented (intervention record files, projects, planning, among others). The results show models, theories and approaches utilization that are relevant according to gendarmerie directions and national and international evidence. However, projects operation conditions are recognized, which tense and limit the work scope developed with young people. The lack of continuity in the work is highlighted as one of these limitations, since the financing conditioned on tenders that happen yearly and that obstruct the teams’ job stability. The interviewees state a set of proposals for improving interventions with young people; among those interventions are: a specialized training of the intervener psychosocial team, including the gendarmerie staff which are in permanent touch with young people; to improve the direct work with young people by incorporating the Canadian original psychological-educational approach to structure in a coherent way interventions of the juvenile sections on daily basis, incorporating a differentiated intervention focus, considering young people crime trajectories, and finally, it underlines the necessity of deepening the social-communitary inclusion component in the interventions.

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)0.005
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.356
Teacher spread0.341 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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