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Record W2015860605 · doi:10.4000/champpenal.7966

Un monde d’homicides

2011· article· fr· W2015860605 on OpenAlex
Marc Ouimet

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChamp pénal · 2011
Typearticle
Languagefr
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Cette étude vise à établir les variations du taux d’homicides entre les pays du monde et à examiner les facteurs qui y sont liés. L’analyse porte sur 167 pays pour lesquels nous disposons en 2004 d’une estimation fiable du taux d’homicides. Les données sur l’homicide proviennent de l’Organisation mondiale de la santé et les données pour les variables explicatives proviennent de sources variées. Les analyses statistiques préliminaires portent sur les caractéristiques populationnelles, économiques, environnementales, sociales, identitaires et politiques des pays. La modélisation statistique finale montre que trois grands facteurs expliquent les variations du taux d’homicides, soit le pourcentage de jeunes dans la population, le niveau de vie tel que mesuré par le PIB et le degré d’inégalité de la redistribution des revenus. En discussion sont abordés les thèmes de la composition de la population, de la situation économique et du système politique.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.012

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 head0.083
GPT teacher head0.322
Teacher spread0.239 · 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