What Relationship Researchers and Relationship Practitioners Wished the Other Knew: Integrating Discovery and Practice in Couple Relationships
Bibliographic record
Abstract
As we consider what both family scientists and practitioners can learn from each other, we discuss important advances in relationship and marriage education (RME). We note best practices for research and review recent evaluative findings from randomized controlled trial studies that have important implications for RME. An almost singular RME focus on teaching communication and conflict resolution skills may not be as valuable as it was believed to be. We discuss recent shifts in RME, share results from recent research, and advocate for a balanced approach that incorporates both skill‐based and principles‐based approaches. Important insights can be gained from disciplines outside of family and relationship science, and we encourage both family scientists and practitioners to broaden the scope of models of healthy relationship functioning. Finally, we offer some direction for future progress and issue a call for more integrative and rigorous efforts in both the science of discovery and practice.
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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 | 0.319 | 0.360 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.054 |
| Scholarly communication | 0.030 | 0.058 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".