Taking the Long View on Science, Metaphysics and Philosophy of Science
Bibliographic record
Abstract
Metaphysics and the Philosophy of Science1 collects contributions that mostly came out of a ground-breaking 2011 conference organized by the editors, with a few extra additions. Since that 2011 conference, discussions have exploded about what the relationships are, or should be, or should not be, or could even be, or have historically been, between all three of metaphysics (analytic metaphysics in particular though not exclusively), philosophy of science and science itself. As such, it is easy to lose sight of just how revolutionary that conference was, and how much careful scholarship and worthwhile ideas there are in this volume. Despite the lag time of 6 years between conference and the publication of this collection, and despite the massive eruption of discussions on this topic, this book contains a great deal of new material notable for its original and careful scholarship. The volume is still stage-setting for the debate in how much it can contribute to these new and ongoing discussions – impressive, given how many chapters predated such discussions. While there is still much to disagree with in this volume, there is also much that is impressively relevant to the leading edge of current discussions and which has useful insight for moving those discussions forward. The contributions here need to be taken into account in any discussion on metaphysics of science.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.021 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.016 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".