Evaluating Convergence of Within-Person Change and Between-Person Age Differences in Age-Heterogeneous Longitudinal Studies
Why this work is in the frame
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Bibliographic record
Abstract
The distinction of between-person age differences from within-person age changes is necessary for understanding aging-related change processes. Although longitudinal studies are required to address issues relating to within person change, most studies begin using age-heterogeneous samples and conclude using survival-heterogeneous samples. Given the numerous potential confounds associated with age-heterogeneous samples, careful treatment of between-person age differences is essential to obtain the correct inferences regarding within-person age change. We demonstrate how failure to differentiate between-person age effects (and by extension, of survival age or other effects producing sample heterogeneity) will lead to uninterpretable inferences regarding within-person change. We recommend that convergence of age differences and age changes be formally evaluated whenever possible.
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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 | 0.007 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it