Conflict resolution patterns and violence perpetration in adolescent couples: A gender‐sensitive mixed‐methods approach
Bibliographic record
Abstract
This study used a sequential two-phase explanatory design. The first phase of this mixed-methods design aimed to explore conflict resolution strategies in adolescent dating couples, and the second phase to document, from both the perspective of the individual and of the couple, dyadic interaction patterns distinguishing youth inflicting dating violence from those who do not. A sample of 39 heterosexual couples (mean age 17.8 years) participated in semi-structured interviews and were observed during a 45 min dyadic interaction. At phase 1, qualitative analysis revealed three main types of conflict resolution strategies: 1) negotiating expectations and individual needs; 2) avoiding conflicts or their resolution; 3) imposing personal needs and rules through the use of violence. At phase 2, we focused on couples with conflictive patterns. Results indicate that couples who inflict violence differ from nonviolent couples by their tendency to experience conflicts when in disagreement and to resort to negative affects as a resolution strategy. In addition, while at an individual level, they show a tendency to withdraw from conflict and to use less positive affect, at a dyadic level they present less symmetry. Results offer important insights for prevention programs.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".