Bibliographic record
Abstract
Abstract A Better Ape explores the evolution of the moral mind from our ancestors with chimpanzees, through the origins of our genus and our species, to the development of behaviorally modern humans who underwent revolutions in agriculture, urbanization, and industrial technology. The book begins, in Part I, by explaining the biological evolution of sympathy and loyalty in great apes and trust and respect in the earliest humans. These moral emotions are the first element of the moral mind. Part II explains the gene-culture co-evolution of norms, emotions, and reasoning in Homo sapiens. Moral norms of harm, kinship, reciprocity, autonomy, and fairness are the second element of the moral mind. A social capacity for interactive moral reasoning is the third element. Part III of the book explains the cultural co-evolution of social institutions and morality. Family, religious, military, political, and economic institutions expanded small bands into large tribes and created more intense social hierarchies through new moral norms of authority and purity. Finally, Part IV explains the rational and cultural evolution of moral progress and moral regress as human societies experienced gains and losses in inclusivity and equality. Moral progress against racism, homophobia, speciesism, sexism, classism, and global injustice depends on integration of privileged and oppressed people in physical space, social roles, and democratic decision making. The central idea in the book is that all these major evolutionary transitions, from ancestral apes to modern societies, and now human survival of climate change, depend on co-evolution between morality, knowledge, and complex social structure.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.072 | 0.016 |
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 source (direct Gemma or distilled Codex), 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".