Independently motivating the KochenDieks modal interpretation of quantum mechanics
Bibliographic record
Abstract
Abstract All interpretations of quantum mechanics still face the issue vigorously debated by Einstein and Bohr in the 1930s: do the theory’s mere probabilistic predictions for measurement outcomes indicate that observables lack definite values prior to measurement? Or is it just that the theory is lacking, making it currently not possible to know with certainty what the true values are until they are measured? Kochen (1985) and Dieks (1989), or ‘KD’ for short, embrace the For countless useful comments and often penetrating criticism, I would like to thank Guido Bacciagaluppi, John L. Bell, Harvey Brown, Jeffrey Bub, Bill Demopoulos, Michael Dickson, Dennis Dieks, Arthur Fine, Martin Jones, Simon Kochen, Richard Healey, Meir Hemmo, David Malament, Hamar Pitowsky, Laura Ruetsche, Abner Shimony, and Howard Stein. (This is not a list of ‘endorsements’.) And I wish to express gratitude to the Social Sciences and Humanities Research Council of Canada for their continued generous support.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".