“Pay Me Back”: Testing the Implications of Long-Term Changes and Partner Similarity in Exchange Orientation Within Intimate Relationships
Bibliographic record
Abstract
Past research on intimate relationships suggests that exchange orientation—the tendency to expect direct reciprocation when providing a benefit—predicts lower relationship well-being. However, limited research has examined the long-term associations of this link or the effects of partner similarity in exchange orientation. The present research addressed this gap by employing a set of rigorous analyses on longitudinal data spanning 13 years from a national sample of romantic couples in Germany ( N = 7,293 couples). Latent curve models with structured residuals (LCM-SR) revealed that romantic partners, on average, experienced a general decline in exchange orientation over the course of their relationship. Partners who showed slower declines in exchange orientation experienced steeper declines in relationship satisfaction. Within-person increases in exchange orientation predicted future decreases in relationship satisfaction. Dyadic response surface analyses (DRSA) indicated no evidence of similarity effects. Overall, these findings corroborate the adverse effects of exchange orientation on 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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".