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Record W4392182586 · doi:10.1037/pac0000721

Colombian youths’ reasoning about retributive and restorative justice in the 2016 peace accord: Associations with trust.

2024· article· en· W4392182586 on OpenAlexfundno aff
Angelica Restrepo, Laura Pareja Conto, Holly Recchia, Roberto Posada, Gabriel Vélez, Cecilia Wainryb

Bibliographic record

VenuePeace and Conflict Journal of Peace Psychology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaConcordia University
KeywordsRestorative justiceRetributive justiceCriminologyPsychologyEconomic JusticeSocial psychologySociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

This study investigated Colombian adolescents’ evaluations and expectations about different solutions to seeking justice in the aftermath of group-based harms and how their judgments of solutions were associated with self-reported levels of trust. In individual interviews, 74 adolescents (M age = 16.48 years; 36 girls, 38 boys) in Bogotá, Colombia were presented with scenarios depicting two forms of group harm (involving damage to infrastructure and loss of life) based on events relevant to the Colombian armed conflict. For each scenario, adolescents rated the desirability and likelihood of five solutions (apologies, compensation by the FARC, compensation by the government, punishment, and a combination of compensation and punishment). Participants also completed a questionnaire assessing their general levels of trust. Compensation by the FARC and the government were more strongly endorsed in the context of damage to infrastructure, whereas punishment was endorsed more in response to loss of life. Youth also expected compensation by the FARC to be more likely to occur for damage to infrastructure, while they believed punishment was more likely for loss of life. Higher levels of trust were associated with support for restorative solutions, particularly in response to loss of life. Youths’ open-ended justifications for their evaluations of different solutions to address the harms reflected varied concerns, including their perceptions of how to meet the needs of victims and communities, ensure accountability for the harms committed, and achieve revenge.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.042
GPT teacher head0.393
Teacher spread0.351 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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