Bibliographic record
Abstract
INTRODUCTION Isaac Levi stands out as one of the most important philosophers who has worked in the pragmatist tradition. Like his predecessors, Charles Peirce, William James, and John Dewey, Levi insists that we must take practice and context seriously when we think about knowledge and truth. Each of the classical pragmatists followed through on this central insight in a different way and each has motivated a different kind of contemporary pragmatist. Levi's kind focusses on according our existing corpus of belief its actual and proper status in epistemology. What we are concerned with in inquiry – in seeking knowledge – is the revision of that corpus of belief as opposed to the pedigree or origin of belief. What we are concerned with is whether we should retain a commitment or whether we should abandon it in favor of an alternative commitment. Levi seems to sometimes take himself to be closest to Dewey, in whose old department – Columbia – Levi spent the bulk of his career. They both focus on the problem-solving nature of knowledge. But it is more apt, I suggest, to think of Levi as the inheritor of Peirce's position. Levi has himself acknowledged the similarities. But he also identifies what he takes to be significant gulfs between his position and Peirce's. My aim in this chapter is to show that these are not as wide as they might first appear.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".