Political context is associated with extent of everyday physiological synchrony in older couples
Bibliographic record
Abstract
Abstract Social units such as couples exist within a broader societal and cultural context. Characteristics of this macro-level context may indirectly shape couple dynamics by influencing opportunities and motivation for interdependence, e.g. through legislation and prevalent norms/values. The current study investigates the association between political context (left-right political spectrum) and physiological linkage (cortisol synchrony) in older couples’ daily lives. Older adult couples (N = 162) aged 56 to 89 years (M age = 72.3 years) and residing in Germany provided salivary cortisol samples 7 times daily for a 7-day period. Political context in which dyads lived was quantified with respect to where the federal state of residence was located on the left-right political spectrum using voting data from the 2017 federal election. Links between macro-context and extent of cortisol synchrony were examined using multilevel models, controlling for differences in diurnal rhythm, sex, age, body mass index, and individual-level political orientation. On average, there was evidence of synchrony in fluctuations in partners’ cortisol (b = 0.08, SE = 0.02, p < .001). The extent of cortisol synchrony was moderated by macro-context, such that couples living in a federal state placed further right on the left-right political spectrum exhibited greater cortisol synchrony (b = 0.03, SE = 0.01, p = .010). This new evidence provides a foundation for theorizing about and investigating how specific mechanisms contributing to political context, including family values, gender role attitudes, and laws supporting gender equality contribute to interpersonal linkages of physiological stress responses in daily life.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".