Bibliographic record
Abstract
Abstract Philosophy is the attempt to answer general questions about the nature of knowledge, reality, and values. Natural philosophy draws heavily on the sciences and finds no room for supernatural entities such as souls, gods, and possible worlds. Paul Thagard develops interconnected theories of knowledge, reality, morality, justice, meaning, and the arts. He uses new theories of brain mechanisms and social interactions to forge original accounts of the traditional branches of philosophy, including epistemology, metaphysics, ethics, and aesthetics. Rather than reducing the humanities to the sciences, this book displays fertile interconnections that show that philosophical questions and artistic practices can be much better understood by considering how human brains operate and interact in social contexts. The sciences and the humanities are interdependent, because both the natural and social sciences cannot avoid questions about methods and values that are primarily the province of philosophy. Rather than diminish philosophy, the goal of this book is to show its importance for diverse human enterprises, including science, politics, the arts, and everyday life. Natural philosophy draws on the sciences to dramatically increase understanding of fundamental issues concerning mind, meaning, and morality. This book belongs to a trio that includes Brain–Mind: From Neurons to Consciousness and Creativity and Mind–Society: From Brains to Social Sciences and Professions. They can be read independently, but together they make up a Treatise on Mind and Society that provides a unified and comprehensive treatment of the cognitive sciences, social sciences, professions, and humanities.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.035 | 0.012 |
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".