Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This is an expanded version of comments on the future of the demography of aging at an invited session of the 2008 annual meeting of the Population Association of America. In an introduction, John Haaga offers reasons for a revival of interest in population aging, including greater realization of plasticity in aging trajectories at both individual and societal levels. Linda Martin proposes that population scientists working in aging emulate those studying fertility and family planning in previous decades, learning from interventions (in this case, aimed at increasing retirement savings and reducing disability at older ages). Changes in family structure will increasingly affect new cohorts of the elderly, and Linda Waite speculates on the ways in which changes in the economy, medicine, and the legal environment could affect the social context for aging. Research on mortality at older ages is “alive and well” asserts James Vaupel, who sets out six large questions on mortality trends and differentials over time and across species. Lastly, Wolfgang Lutz expands the scope of projections, showing the considerable uncertainty about the timing and pace of population aging in the developing world and the effects on future elderly of the increases in educational attainment in much of the world during the second half of the twentieth century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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