Intraindividual Variability and Empathic Accuracy for Happiness in Older Couples
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. Empathic accuracy involves identifying the emotions of others. Most evidence is based on younger samples, which is limiting because of well-established motivational shifts that occur in older adulthood. Here, we examine associations between fluctuations in happiness and empathic accuracy, using momentary assessments of happiness from 107 couples ( M age = 75.2) in Berlin (Germany; up to 42 assessments) and 117 couples ( M age = 71.1) in Vancouver (Canada; up to 28 assessments). Coordinated analyses show that perceivers are more accurate when they themselves have high happiness variability (Berlin, Vancouver). Target happiness variability did not moderate accuracy slopes. Follow-up analyses explore the role of partners sharing their feelings. Examining moderators of empathic pattern accuracy extends our understanding of positive socioemotional functioning in older couples.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it