We are in this together
Bibliographic record
Abstract
Lifespan theoretical notions have long acknowledged that regulative capacities of the self are relatively robust well into old age. This general trend notwithstanding, people often differ substantially throughout life in their levels of and change trajectories in self-esteem. One prime contributing factor may be perceptions of social inclusion. Because functioning and development in many domains of life are often linked across partners, we examine whether and how self-esteem and its late-life change are intertwined between long-term married partners. To do so, we make use of six occasions over 18-year longitudinal data from 382 married couples in the Australian Longitudinal Study of Aging ( M age = 75 years at baseline, SD = 5.3, range 65–91). Applying SEM-based continuous time panel models revealed that discrete time autoregressive effects, which capture the stability of self-esteem, were declining over time. Most important for our question, across-partner (cross-lagged) effects indicated substantial differences between spouses such that change in husbands’ self-esteem predicts subsequent changes in the wives’ self-esteem, but not vice versa. We discuss potential conditions and challenges of dyadic associations in how late-life self-esteem and its change are intertwined between partners.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.146 | 0.075 |
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".