Usage problématique de la pornographie : conceptualisation, évaluation et traitement
Bibliographic record
Abstract
La facilité d’accès à Internet a une grande incidence sur l'usage de la pornographie. Certaines personnes éprouvent toutefois des difficultés à gérer leur usage, ce qui amène plusieurs conséquences dans leur fonctionnement au quotidien. L’usage problématique de la pornographie étant un phénomène récent, les psychologues, sexologues et intervenants en santé mentale ne sont pas toujours outillés pour intervenir efficacement sur cette problématique. Comment comprendre, évaluer et traiter cette problématique? L’objectif de cet article est de dresser l’état des connaissances actuelles sur l'usage problématique de la pornographie, sur les méthodes d'évaluation documentées et les traitements et approches cliniques d’intervention possibles afin de guider les professionnels à mieux intervenir auprès d’une clientèle aux prises avec cette problématique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".