Bibliographic record
Abstract
At the time of writing, Noam Chomsky has produced over eighty books, hundreds of articles, and thousands of speeches. He has given thousands of interviews, written countless letters, and supervised scores of theses. He has made important, sometimes groundbreaking, contributions to three areas - linguistics, philosophy of mind and human nature, and politics. He set linguistics on a successful naturalistic, biologically oriented scientific course; his theoretical contributions continue to lead the field. Like Descartes, Galileo, and Hume, and unlike the eighteenth-century philosopher Kant and the great majority of philosophers thereafter, Chomsky is both scientist and philosopher, and his philosophical work is continuous with his scientific. His science of language and incipient science of mind offer a genuine prospect of coming to a biologically based grasp of human nature and of the way it allows for human understanding and action. His political work, like both Hobbes’s and Rousseau's, seeks a foundation in a science of human nature, although with better prospects for developing such a theory - and for exploring its implications for political ideals and goals - than Hobbes’s misguided attempt to construct a causal theory of human action or Rousseau’s fanciful assays into a “state of nature.” And unlike both of them - and far too many contemporary political “theorists” - there is no sign in Chomsky’s political work that his views and critical analyses are driven by a wish for power.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.420 | 0.253 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".