Bibliographic record
Abstract
In one of the excerpts from memory composing his autobiography, Stanley Cavell recalls attending “an informal but extended discussion among professional philosophers” with Thomas Kuhn, then his colleague at Berkeley. It was the first such meeting the two friends had sat through together, and Cavell describes the vivid impression left on the historian of science: “As we left the scene Kuhn pressed his fingers to his forehead as if it ached. ‘I wouldn’t have believed it. You people don’t behave like academics in any other field. You treat each other as if you are all mad.’” The perception, Cavell notes, “seemed right […] but normal enough, and because normal, suddenly revelatory.” Kuhn’s response clearly anticipates topics and arguments that would come to inform The Structure of Scientific Revolutions. Articulated within the terms of those arguments, the exasperating scene becomes one of philosophical discussion in the absence of a paradigm, unable to take place upon an assumed common ground.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.013 | 0.023 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.012 | 0.023 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".