Bibliographic record
Abstract
Like most books in philosophy, Communicative Action and Rational Choice contains a large number of arguments (six big ones, by my count, plus dozens of smaller ones). Each of these arguments I adhere to with a greater or lesser degree of conviction. Some of them I think are pretty decisive. In other cases, I was doing the philosophical equivalent of throwing things against the wall just to see what sticks. Of course, I did not present things that way in the book, choosing instead to dress up my scruffier arguments in the hope that they might appear to share the same pedigree as my more refined ones. It is thus a testament to the astuteness of my critics here that they have focused their criticism almost entirely on my more tentative arguments—especially my so-called “pragmatic theory of convergence,” which is less a theory than a set of suggestions about how a theory might be constructed. Thus my desire to defend these arguments against criticism, which predominates in what follows, should be understood also as tempered by the recognition that much of what I say may ultimately prove to be unsustainable.
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 | 0.027 | 0.158 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.099 | 0.107 |
| Insufficient payload (model declined to judge) | 0.021 | 0.016 |
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".