MétaCan
Menu
Back to cohort
Record W34348514 · doi:10.1177/00187208211033450

Reinserción laboral y antecedentes penales

2011· article· en· W34348514 on OpenAlexfundno aff
Elena Larrauri, James B. Jacobs

Bibliographic record

VenueRevista electrónica de ciencia penal y criminología · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Penology
Canadian institutionsnot available
FundersCanada First Research Excellence FundNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Este articulo asume que los antecedentes penales suponen un serio obtaculo para la reintegracion laboral de las personas que han cumplido una condena. Se presume que esta reinsercion es mas dificil en los paises en que se dan tres condiciones: los antecedentes penales son publicos y facilmente accesibles, los empresarios estan obligados a llevar a cabo controles antes de contratar a sus empleados, y los antecedentes penales no se cancelan. El articulo se centra en la legislacion espanola referida a los empleos para los cuales se exige la presentacion de un certificado de antecedentes penales (CAP), e intenta averiguar en que casos esta permitido solicitarlos y en cuales esta prohibido. Dado que en el ano 2010 se han realizado un millon y medio de peticiones al Registro Central de Penados (RCP) en Espana nuestra duda es si tambien aqui los antecentes penales representan un mayor obstaculo del imaginado a la reinsercion laboral.

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)0.001
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 score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.132
GPT teacher head0.343
Teacher spread0.211 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueRevista electrónica de ciencia penal y criminologíaSame topicCriminal Justice and PenologyFrench-language works237,207