Long Distance Dating Relationships: Do People in Them Really Experience Less Sexual and Relationship Satisfaction, Intimacy, Love, and Sexual Communication?
Bibliographic record
Abstract
Despite the high prevalence of long distance dating relationships (LDDRs), they have been understudied, and many facets remain unexplored. Previous studies examined variables such as idealization, communication, and relationship satisfaction, but many contradictory results exist. Furthermore, no studies thus far have examined sexuality and how it is impacted by long distance. The purpose of this study is to examine differences in various relationship and sexual characteristics between individuals in LDDRs and in geographically close relationships (GCRs). Gender differences will also be examined. Participants are invited to visit a secure website that contains online questionnaires. The main outcomes variables are intimacy, communication, sexual and relationship satisfaction, and love. Two main research questions will be investigated: (1) whether there are differences between individuals in LDDRs and GCRs on the outcome variables, and (2) if distance apart/frequency of face‐to‐face contact predicts sexual and relationship satisfaction, intimacy, and communication for couples in LDDRs. It is expected that individuals in LDDRs will have lower relationship adjustment and sexual satisfaction than those in GCRs. In addition, it is expected that females will score higher on measures of sexual and relationship satisfaction, love, and intimacy than males, regardless of relationship type. Furthermore, it is expected that greater distance apart/lower frequency of contact will predict negative outcomes in the aforementioned variables, and that love and attitude towards LDDRs will mediate these relationships. This study is currently ongoing, and results will be presented.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".