Bibliographic record
Abstract
Like many important philosophers around the turn of the last century, Russell came to philosophy from mathematics. From 1890 to 1893 he studied for Part I of the Cambridge Mathematical Tripos, as the Cambridge examination was called. That he started with mathematics was inevitable: all Cambridge students had to take either classics or mathematics for Part I of their degree, and Russell was neither good at, nor interested in, classics. Nonetheless, mathematics recommended itself to Russell for other reasons than necessity. He went up to Cambridge with the hope of discovering what, if anything, could be known with certainty and with the conviction that, if anything could, it would be found in mathematics. These high hopes were rapidly dashed by the realities of the Tripos. The fact that so many students with differing interests had to take mathematics at Cambridge meant that the mathematics taught was relatively elementary and strongly oriented to physical application and geometrical intuition. Not that the Mathematical Tripos was easy; study for it was a relentless grind of practice in the solution of mathematically trivial, but fiendishly complicated, applications problems. The great developments of nineteenth-century mathematics, for example, in analysis and non-Euclidean geometry, and all the developments mentioned by Grattan-Guinness in his paper in this volume, were entirely ignored as unsuitable to the needs of most students. In particular, the nineteenth-century drive towards rigour and unification in mathematics was absent from Cambridge, which, despite its continuing high reputation in the subject, had become a mathematical backwater by the end of the century.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".