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Record W2738788476 · doi:10.37260/rctd.v2i3.33

NUEVO CODIGO PENAL PARA AFRONTAR LOS RETOS DE LAS MODALIDADES DELICTIVAS DEL SIGLO XXI

2016· article· es· W2738788476 on OpenAlexaff
Henry A. Guillén Sosa

Bibliographic record

VenueRevista ciencia y tecnología para el desarrollo UJCM. · 2016
Typearticle
Languagees
FieldSocial Sciences
TopicCriminal Justice and Penology
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

La presente revisión tiene el propósito de relacionar el derecho penal moderno cuestionando algunas instituciones jurídicas y concepciones punitivas que no son útiles dentro del Código Penal promulgado en 1991, A casi un cuarto de siglo de los cambios producidos, el Código Penal ha sufrido una seria afectación jurídica y no concordante con un necesario nuevo Código Penal para sancionar las conductas delictivas del siglo XXI, en las actuales circunstancias el Código Penal del Perú promulgado en 1991 ha devenido en obsoleto e insuficiente para combatir con éxito los delitos modernos. El código penal vigente tiene un total de 195 afectaciones jurídicas (terminología jurídica), es decir, que un 43,14 % ha sido modificado, lo cual consideramos excesivo. Es evidente que un nuevo código no va a solucionar el crimen organizado y todas sus variantes delictivas, pero este instrumento legal es necesario para combatirlo, por esto, es recomendable elaborar un nuevo código penal con participación de expertos, entre ellos, los designados por universidades, colegios de abogados y juristas calificados. Finalmente, el nuevo código para el Perú debe considerar el Preámbulo del Estatuto de Roma y, transitoriamente, debe comisionarse a expertos para redactar un Texto Único Concordado del Código Penal vigente.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.052
GPT teacher head0.352
Teacher spread0.300 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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