Satisfaction or connectivity?: Implications from the strong relationality model of flourishing couple relationships
Bibliographic record
Abstract
A central feature of couple relationships research is the use of self-report measures of relationship satisfaction. Despite the widespread use of such measures in couples' research, scholars have raised critical questions about satisfaction-focused assessment, including concerns about taking an ontologically individualistic focus. Moving beyond ontological individualism, drawing from the Strong Relationality Model of Relationship Flourishing and data from 615 couples in the United States and Canada (N = 1230 individuals), we explored similarities and differences between assessments of relationship satisfaction and a measure based on strong relationality (relational-connectivity). We evaluated associations with other scales assessing relationship factors including indicators of well-being, relationship processes, virtues, and responsible actions. Using confirmatory latent profile analysis, we classified individuals as Flourishing (55.4%), Languishing (31.8%), Connected, Less-Satisfied (7.8%), or Satisfied, Less-Connected (5.0%). Our results suggest that attending to richer perspectives of relationship quality may spur additional understanding of many factors associated with meaningful couple 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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| 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".