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
Human evolutionary demography is an emerging field blending natural science with social science. This edited volume provides a much-needed, interdisciplinary introduction to the field and highlights cutting-edge research for interested readers and researchers in demography, the evolutionary behavioural sciences, biology, and related disciplines. By bridging the boundaries between social and biological sciences, the volume stresses the importance of a unified understanding of both in order to grasp past and current demographic patterns. Demographic traits, and traits related to demographic outcomes, including fertility and mortality rates, marriage, parental care, menopause, and cooperative behavior are subject to evolutionary processes. Bringing an understanding of evolution into demography therefore incorporates valuable insights into this field; just as knowledge of demography is key to understanding evolutionary processes. By asking questions about old patterns from a new perspective, the volume—composed of contributions from established and early-career academics—demonstrates that a combination of social science research and evolutionary theory offers holistic understandings and approaches that benefit both fields. Human Evolutionary Demography introduces an emerging field in an accessible style. It is suitable for graduate courses in demography, as well as upper-level undergraduates. Its range of research is sure to be of interest to academics working on demographic topics (anthropologists, sociologists, demographers), natural scientists working on evolutionary processes, and disciplines which cross-cut natural and social science, such as evolutionary psychology, human behavioral ecology, cultural evolution, and evolutionary medicine. As an accessible introduction, it should interest readers whether or not they are currently familiar with human evolutionary demography.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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