Bibliographic record
Abstract
Abstract Empiricisms reassesses the values of experience and experiment in European philosophy and comparatively. It traces the history of empirical philosophy from its birth in Greek medicine to its emergence as a philosophy of modern science. A richly detailed account in Part I of history’s empiricisms establishes a context in Part II for reconsidering the work of the so-called radical empiricists—William James, Henri Bergson, John Dewey, and Gilles Deleuze, each treated in a dedicated chapter. What is “radical” about their work is to return empiricism from epistemology to the ontology and natural philosophy where it began. Empiricisms also sets empirical philosophy in conversation with Chinese tradition, considering technological, scientific, medical, and alchemical sources, as well as selected Confucian, Daoist, and Mohist classics. The work shows how philosophical reflection on experience and a profound experimental practice coexist in traditional China with no interaction or even awareness of each other. Empiricism is more multi-textured than philosophers tend to assume when we explain it to ourselves and to students. One purpose of Empiricisms is to recover the neglected context. A complementary purpose is to elucidate the value of experience and arrive at some idea of what is living and dead in philosophical empiricism.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.051 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".