Russell’s Concepts “Name”, “Existence” and “Unique Object of Reference” in Light of Modern Physics
Bibliographic record
Abstract
With his theory of descriptions Russell wanted to solve two problems concerning denotation and reference, which are formulated here as Problem I and Problem II. After presenting each problem, we describe the main points of Russell’s solution. We deal with Russell’s concepts of existence and then elaborate his presuppositions concerning the relation of denoting and referring. Next we discuss the presuppositions or principles which underlie Russell’s understanding of the objects of reference. These principles are such that if the objects of reference are material objects, they are objects of classical mechanics, or very close to such an interpretation. Finally we show how these principles have to be relaxed if the objects of reference are objects of quantum mechanics or special or general relativity.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.005 | 0.018 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| 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".