A qualitative analysis of themes in long-distance couples’ relationship boundary discussions
Bibliographic record
Abstract
Many couples have explicit discussions regarding the emotional and sexual boundaries in their relationship, which can benefit their relational and sexual health. However, the implicit assumption in health research that couples discuss relationship boundaries to protect their sexual health is counter to evidence that many couples discuss boundaries to increase trust, closeness, and intimacy. We examined long-distance partners’ reasons for discussing boundaries and used an approach and avoidance framework to understand motives. Individuals in long-distance relationships ( N = 77 couples) described their relationship boundaries, what prompted their discussion about boundaries, and the goal of their discussion. We thematically analyzed their motives for the discussion as either approach or avoidance and identified sub-themes that emerged within the larger category of approach and avoidance motives. Most participants had discussed boundaries multiple times with their partner, and about one-third identified a specific event that triggered their discussion. A minority of individuals were motivated to discuss boundaries with their partner to avoid aversive outcomes (i.e., avoidance motives), but no participants reported motives to mitigate sexual health risks. Instead, most participants anticipated gaining individual and relational benefits from their discussion about boundaries (i.e., approach motives), which suggests that couples might be more motivated by what they have to gain by discussing boundaries and are not explicitly motivated to mitigate sexual health risks.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".