Ordinary Language Problem and Quantum Reality
Bibliographic record
Abstract
Language has severally been viewed as a collection of words, phrases, and sentences. For some, it is a habit system, acquired accidentally and extrinsically. It is further regarded as a structure of forms and concepts based on a system of rules that determine their interrelations, arrangement, and organization. Language also has a relationship with the world and how we talk about the world. It is often likened to a tool, perhaps man’s most important one; more useful it seems than fire, the wheel, or atomic energy. However, language like any tool has its limitations. This limitation is very obvious in the discussions of the behavior of sub-atomic quantum particles of reality since the ordinary everyday language of this macro-world does not fit into the picture of the behavior of elementary particles of physics. This paper attempts to highlight the language difficulties inherent in the discussions of quantum reality from a philosophical perspective using such tools as criticism, analysis and speculation to justify the position that ordinary language is not enough to interpret and explain quantum reality.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.004 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 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".