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
The human propensity to take an ethical stance toward oneself and others is found in every known society, yet we also know that values taken for granted in one society can contradict those in another. Does ethical life arise from human nature itself? Is it a universal human trait? Or is it a product of one's cultural and historical context? This book offers a new approach to the empirical study of ethical life that reconciles these questions, showing how ethics arise at the intersection of human biology and social dynamics. Drawing on the latest findings in psychology, conversational interaction, ethnography, and history, the book takes readers from inner city America to Samoa and the Inuit Arctic to reveal how we are creatures of our biology as well as our history—and how our ethical lives are contingent on both. The book looks at Melanesian theories of mind and the training of Buddhist monks, and discusses important social causes such as the British abolitionist movement and American feminism. It explores how styles of child rearing, notions of the person, and moral codes in different communities elaborate on certain basic human tendencies while suppressing or ignoring others. Certain to provoke debate, the book presents an entirely new way of thinking about ethics, morals, and the factors that shape them.
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 | 0.000 | 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 | 0.001 | 0.001 |
| 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