Helping men build better intimate partner relationships: Canadian provider perspectives
Bibliographic record
Abstract
Objective: The aim of this study was to describe the strategies used by Canadian healthcare providers to assist men in strengthening their intimate partner relationships. Design: Qualitative research study. Method: Data were collected through semi-structured individual interviews. Using interpretive descriptive methods, secondary analysis inductively identified the strategies used by 10 Canadian-based healthcare providers. Participants comprised six counsellors, one registered psychologist, one associate certified coach, one father support supervisor and one programme facilitator. Result: Three thematic findings were developed: (1) equipping men with lifelong relationship skills; (2) knowing and transforming masculinities; and (3) understanding men’s experiences using trauma-informed care approaches. Theme 1 stressed the importance of attentively listening for cues, establishing dialogue and expressing emotions to meet men’s needs. Emphasised was the need to create safe spaces and respect men’s disclosures about previous intimate partner experiences. Theme 2 highlighted the significance of knowing and transforming masculinities to promote pro-social values by identifying and mobilising men’s strengths and assets. Providers explored attitudes about masculinity and created opportunities for men to model transformative approaches towards equitable relationships. Theme 3 emphasised the need to better understand men’s trauma in order to situate and progress their intimate partner relationships. By acknowledging men’s trauma, providers aimed to undo harmful patterns of emotional suppression and facilitate progress towards healing. Conclusion: This study identities strategies for working with men to promote emotional reflexivity, pro-social behaviour and help-seeking in intimate partner relationships.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".