Understanding barriers to sexual communication
Bibliographic record
Abstract
There is consistent empirical evidence to suggest that more open and positive sexual communication is a vital component of sexual relationships, but romantic partners tend to avoid sexual communication. Although clinical and theoretical writing has identified barriers to sexual communication, there is a relative paucity of empirical literature investigating specific barriers to sexual communication and whether these barriers are unique to sexual communication. We developed the Barriers to Communication Questionnaire, a measure that investigates the types of threat that are activated during couples’ sexual and nonsexual communication (Study 1) and the degree to which these threats are differentially activated across the two discussions (Study 2). In Study 1, we found that the same categories of threats were activated for both sexual and nonsexual conflict communication: threat to self, threat to partner, and threat to relationship. Study 2 revealed that threat to self is activated to a greater degree during sexual conflict communication compared to nonsexual conflict communication. The differential degree to which threat to self is activated during sexual and nonsexual communication provides a plausible explanation for why romantic partners tend to avoid sexual communication more so than nonsexual communication. The measure developed in the current study could be used clinically to identify the specific threats that are preventing an individual from communicating with the partner about needs and desires. In the research domain, the measure can be used to further investigate the causal association between emotional barriers and sexual communication.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".