MétaCan
Menu
Back to cohort

On the Difference Between Omission Criminal Made and Accomplice

2010· article· en· W1890757439 on OpenAlex
Qiu-hua Hong

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian social science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsViewpointsHumanitiesPhilosophyCriminal lawCompromisePolitical scienceLawArt

Abstract

fetched live from OpenAlex

There has been formed many viewpoints in criminal law world regarding the issue of how to distinguish omission criminal made and accomplice; in general, however, they can be classified into three categories of principle criminal made theory, principle accomplice theory, and compromise theory. Although these three types of viewpoints have both advantages and drawbacks as well; on the whole, they are unable to propose satisfactory answers on how to differentiate omission criminal made and accomplice. In view of this, author, with the hope to settle this issue, present his unique opinion from Pflichtdelikt and dominated committed perspective. Keywords: omission; criminal made; accomplice; dominated committed; PflichtdeliktResume: Afin de faire la question de differenciation avec le complice d'inaction, des cercles de loi de châtiments ont forme un grand nombre de vues a ce sujet. Mais on peut diviser ces vues en trois categories: le principe qui fait, le principe qui permet de faire et le principe qui compromet. Ces trois types de vue ont leurs avantages et leurs defauts. Pourtant, ces trois types de vue ne peuvent pas donner une reponse satisfaisante pour distinguer le complice d'inaction. Pour cette raison, dans l'espoir de resoudre ce probleme, je voudrais faire l'introduction, l'evaluation et l'analyse de ces trois types de vues, et proposer mon propre point de vue de faire et de controler l'angle qui est fait volontairement.Mots-cles: omission, criminel, complice, devoir delit commis domine

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.055
GPT teacher head0.346
Teacher spread0.291 · 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