Les termes prévenu et accusé en droit pénal français, canadien et suisse et leurs équivalents roumains
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.
Bibliographic record
Abstract
In French criminal law, the various procedural statuses of (alledged) offenders are highly nuanced: suspect, témoin, témoin assisté, mis en examen, prévenu, accusé , etc. The concepts operationalised in this respect in the codes (Code pénal and Code de procédure pénale in partic ular) are not systematically defined, but the oppositions that structure this terminological field can easily be approached with the help of contexts and cotexts (the study of collocations proves very promising in this respect). The same is true of the opposition that is the focus of our research (prévenu vs. accusé). e two notions are culturally marked: our study will explore the differences in use (and therefore in conceptualisation / designation) of the two terms in French, Swiss and Canadian criminal law, while evoking the intercultural Romanian equivalents of the terminological system from which they derive.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it