Defying Tradition
Bibliographic record
Abstract
The marriage–health association has been investigated extensively among proximal couples (i.e., those living geographically near each other). On average, married men trend toward better health and relationship outcomes from their marital status compared to married women. This may be attributed to gender role socialization that encourages women to adopt a caretaking role toward their partners. Current literature has not addressed whether there are differential relationship or health outcomes by gender within long-distance relationship (LDR). The present study investigated LDR relationship and health indices by gender. Using Qualtrics and Amazon’s Mechanical Turk, married LDR participants ( n = 93, 21 years or older, English speakers) completed an online survey. Relationship measures assessed satisfaction, maintenance, stress, and sex. Health variables included the Patient Reported Outcomes Measurement Information System-29, Perceived Stress Scale, and surveys examining substance use, diet, and exercise. t Tests were used to measure group differences by gender. Women in LDR reported few relationship and health benefits relative to men in LDR. Men reported higher levels of relational distress and increased smoking, yet better physical functioning. Men also trended toward higher levels of relational maintenance and healthier eating as a function of partner presence. This study provides counterevidence for the gender role socialization model within the LDR framework.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.044 | 0.011 |
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".