Age-related changes in older adults’ anger and sadness: The role of perceived control.
Bibliographic record
Abstract
= 5.81). At each of six waves, participants' levels of sadness, anger, perceived control, and sociodemographic characteristics were assessed. Hierarchical linear modeling demonstrated that sadness, but not anger, linearly increased over time. These increases in sadness were evident only among older adults who reported low (but not high) levels of perceived control across the study period, and who experienced longitudinal declines (but not increases) in perceived control. In addition, nonlinear within-person reductions in perceived control predicted participants' sadness in the entire sample, but were associated with anger only in early, and not in advanced, old age. These findings support the discrete emotion theory of affective aging by documenting the distinctiveness of older adults' anger and sadness. These two negative emotions differ in terms of both age-related changes and predictive person-related perceptions of control. (PsycINFO Database Record
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".