The Pragmatics of Empirical AdequacyThanks are due to the Social Sciences and Humanities Research Council of Canada, and to the University of Melbourne for support of this research. This paper has benefited from discussion with members of the Philosophy and History and Philosophy of Science departments at the University of Melbourne and the Philosophy department at La Trobe University, as well as from the comments and suggestions of three anonymous referees.
Bibliographic record
Abstract
Empirical adequacy is a central notion in van Fraassen's empiricist view of science. I argue that van Fraassen's account of empirical adequacy in terms of a partial isomorphism between certain structures in some model(s) of the theory and certain actual structures (the observables) in the world, is untenable. The empirical adequacy of a theory can only be tested in the context of an accepted practice of observation. But because the theory itself does not determine the correct practice of observation, its failure to pass the test does not show the failure of an isomorphism between the empirical substructure of some model(s) of the theory and observable structures in nature. Further, because the choice of a practice of observation is a pragmatic one grounded in epistemic goals we seek in observation, van Fraassen's anthropocentric view of observability is epistemically unmotivated.
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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 | 0.064 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.010 | 0.023 |
| Scholarly communication | 0.011 | 0.029 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".