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Record W1587811333

Innovación psicosocial: aplicación de un plan de prevención de la delincuencia juvenil

2012· article· es· W1587811333 on OpenAlexaff
Line Leblanc, Marie Robert

Bibliographic record

VenueRepositorio Institucional (Pontificia Universidad Javeriana) · 2012
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsJuvenile delinquencyCompromisePsychosocialFidelityPsychologyIntervention (counseling)SociologyPromotion (chess)Social psychologyWelfare economicsCriminologyPolitical sciencePsychotherapistSocial scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Evidence-based psychosocial treatments for the prevention of juvenile delinquency emphasize the importance of a high quality social environment. However the promotion of this approach in real life is somewhat hindered by diffusion-related problems associated with psychosocial innovation. Indeed, communication between researchers, policy makers, clinicians and members of the community is not an easy task. The communication gap between research and practice is an important issue because its failure could compromise the impact of the intervention on youths at risk of juvenile delinquency. The objective of this article is to put forth a conceptual framework based on theory of diffusion of innovation specifically geared towards optimizing the cohesion between the scientific, politic and practice worlds.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.019
GPT teacher head0.227
Teacher spread0.207 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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