Change in Daily Negative Affect Across 20 Years
Bibliographic record
Abstract
Abstract The current study examined levels of daily NA among people (N=413) who participated in three waves of the National Study of Daily Experiences (~1996; ~2008; ~2017). At each wave, participants reported how often they had experienced six negative emotional experiences every day for eight consecutive days. Cross-sectional analyses at each time-point show age-related decreases in NA. Trajectories over time, however, were moderated by age (Est = .006, SE = .002, p = .001), revealing a curvilinear pattern. Among people who were 25-50 years-old at the first wave, daily NA decreased over time, with decreases more pronounced among the younger adults. For people at least 50 years-old at the start of the study, daily NA increased over time, with the slopes steepest for older adults. Findings indicate that cross-sectional and longitudinal age-related patterns in NA differ when examining data collected from 1996 to 2017.
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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 | 0.003 |
| 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 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".