The cosmological divergent proliferation in Feyerabend's pluralism
Bibliographic record
Abstract
In this paper, I argue that Feyerabendian proliferation is best understood as cosmologically divergent proliferation. The divergent aspect is inspired by a Darwinian background, and it affects other elements of Feyerabend’s philosophy, as much as the way his pluralism advances, like the cosmological dimension. This cosmological item influences not only how theories should proliferate - divergently - but also why they must be tenaciously retained and compared. On this account, we underline Feyerabend’s view that the principle of proliferation is never alone; instead, it is always coupled with the principle of tenacity. This is the reason we take these two principles as two sides of the same coin. Moreover, when approaching tenacity, we discuss three aspects of tenacity (attractiveness, fruitfulness, and retainment) under two forms of how they are related to the cosmologically divergent proliferation. First, working on many cosmologies, allowed by proliferation, to develop them. Second, retaining all theories by what is called a practical suspension or setback. As a result, we argue that such an approach, divergent pluralism, is an adequate way for understanding Feyerabend’s pluralism and a clear way of avoiding misunderstandings of his view.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".