Sexual minority men’s experiences of, and strategies for emotional intimacy in intimate partner relationships
Bibliographic record
Abstract
Emotional intimacy is key to intimate partner relationship quality and satisfaction. For sexual minority men, queer and feminist theorists consistently link emotional intimacy to diverse sexual practices and partnership dynamics formulated within the relationship. This Photovoice study adds to those insights by drawing on individual photovoice interviews with 16 sexual minority men to describe participant's experiences of, and strategies for emotional intimacy in their intimate relationships. Analysis revealed three distinct yet entwined themes: (i) embracing vulnerabilities to drive self-acceptance; (ii) building relationality with partners; and (iii) securing connections with family, friends and community. By embracing vulnerabilities to drive self-acceptance, participants spoke to embodied courage and autonomy as key components for addressing wide-ranging emotional intimacy challenges in their relationships. In theme two, building relationality with partners, participants described how empathy, trust and reciprocity underpinned collaborative work to foster emotional intimacy. Lastly, in securing connections with family, friends and community, acceptance and inclusion were key to participants' sense of belonging and legitimacy which aided their emotional intimacy with partners. The findings provide guidance for tailored programmatic efforts to assist sexual minority men build intimate 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".