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Record W7006868097

Violences sexuelles et droit pénal : perspectives franco-canadiennes Sexual violence and penal law: Franco-Canadian perspectives

2019· other· fr· W7006868097 on OpenAlexaboutno aff

Bibliographic record

VenueOpenEdition (OpenEdition) · 2019
Typeother
Languagefr
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSexual violenceSexual abuseDomestic violenceHuman sexualityGovernment (linguistics)Field (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

La visibilité des luttes contre les violences sexuelles envers les femmes et les enfants s’est accrue ces dernières années. En particulier, depuis le mouvement #MeToo, la multiplicité des violences sexuelles dont les femmes sont victimes fait l’objet de mobilisations collectives, de contestations et de préoccupations sociales intenses. La question du consentement à l’acte sexuel y occupe une place centrale. La réponse des pouvoirs publics à ces préoccupations se formule notamment dans les termes du droit pénal et de son application. C’est cette réponse pénale, dans les contextes français et canadien, qui fait l’objet de la présente journée d’études. Quels sont l’état du droit et des pratiques judiciaires, et à quels écueils se heurtent-ils ? Le consentement sexuel est-il, et peut-il être, un critère légal opératoire dans les pratiques ? In fine, la réponse pénale contemporaine est-elle un instrument adapté pour lutter contre les violences sexuelles ?

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.010
Science and technology studies0.0120.007
Scholarly communication0.0080.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.000

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractno

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