Bibliographic record
Abstract
The causal property identity thesis Causal properties are the fulcrum of semirealism. Their relations compose the concrete structures that are the primary subject matters of a tenable scientific realism. They regularly cohere to form interesting units, and these groupings make up the particulars investigated by the sciences and described by scientific theories. The continuous manifestations of the dispositions they confer constitute the causal processes to which empirical investigations become connected, so as to produce knowledge of the things they study. Scientific realists reach beyond the observable to claim knowledge of certain unobservable properties, structures, and particulars, and by doing so enter the speculative waters of metaphysics. Unlike some metaphysical commitments, being a realist does not require a wetsuit or an oxygen tank, but as I have suggested before, it is not surprising that many realists are not content merely to wade in the shallows. The portrait of realism sketched in Part I places a great deal of weight on certain metaphysical supports, and I have set out to demonstrate the internal coherence of the position by elaborating a unified account of these underpinnings, pointing out along the way certain comparisons to other possibilities with respect to capacities for explanation. Earlier I suggested that the most important aspects of the metaphysical foundations of realism are the idea of causation and the idea of natural categories of things, or kinds. I began a consideration of these issues by examining the nature of causation.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.042 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".