Bibliographic record
Abstract
There are three major ideas arising from Russell's work in logic and philosophy of mathematics which he believed to be of philosophical importance for the theory of our knowledge of the physical world. The first was his theory of descriptions; the second, the concept of structure; and the third, the notion of a logical construction. The use of logical constructions in theory of knowledge was most prominent during Russell's phenomenalist period, the period which culminated with Knowledge of the External World. This phase of Russell's thought falls outside the purview of the present work. Logical constructions play an important - but very different - role in his subsequent realism, where they occur mainly in connection with the “interpretation” of the theory of space-time, and where they subserve both metaphysical and epistemological goals. Although we will have occasion to refer to this application of logical constructions toward the very end of the essay, considerations of space prevent us from exploring their use in any detail. Our focus here will be on the second of these ideas - the concept of structure - and the development of Russell's “structuralism.” But before turning to this topic, it will be worthwhile to sketch Russell’s application of his theory of descriptions to theory of knowledge; this application and his structuralism are often discussed together with the result that they are not always as sharply distinguished from one another as they should be.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".