Violence économique et stratégie de contrôle chez les couples où l'homme est joueur problèmatique
Bibliographic record
Abstract
Gambling problems of one of the life partners bring consequences on conjugal life, including a deterioration of finances. In this context, partners may adopt control behaviors over the household finances. What strategies do partners of problem gamblers use to control their partner's gambling habits and expenses? Are these behaviors similar to economic conjugal violence? To explore these questions, telephone interviews were conducted with 156 women, 54 of which perceived their partner as having a gambling problem. Results showed that a greater proportion of women in a relationship with a problem gambler reported having committed and experienced economic violence behaviors. Some contexts and motives associated with economic violence perpetrated by women lend support to a protective function. Women consider that their partner's economic violence behaviors were aimed at ensuring continuation of gambling activities. Moreover, nearly 80% of women concerned with their partner's gambling habits used strategies to control their gambling habits, including gambling expenditure. The complexity of assessing economic conjugal violence within a problem gambling context is discussed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".