Bibliographic record
Abstract
Abstract One of contemporary pragmatism’s most lively intramural debates is about the status, priority, and emphasis that pragmatism should place on experience, on the one hand, versus language, on the other. Recently, an experientialist pragmatist has argued that the experience–language debate is not ‘really’ about issues of language and experience, but is rather a proxy for another issue: namely, pragmatism’s stance toward the practical world of everyday life and commitment to improving it. In other words, a commitment to meliorism. In this paper I argue that this strategy for cornering the linguistic pragmatist does not work, and that meliorism is not what the language versus experience debate is ‘really about’. First, I argue that the debate is not a proxy for a debate about meliorism, but rather is about exactly what it purports to be about: the place of language and experience in an account of the most basic features of what it is to be the kind of beings we are in the world in which we live. Second, I argue that one’s stance toward meliorism need not covary with whether one embraces either linguistic or experientialist pragmatism. Finally, I argue that to think that pragmatism must begin with meliorism is to put the cart before the horse. My aim is to clarify the import of the experience–language debate and direct the future of that debate back towards other, more fruitful paths recently opened up: those whose destination is overcoming the dichotomy by finding the right way to combine the best insights of both sides of the debate.
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 | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.075 |
| Scholarly communication | 0.021 | 0.026 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".