Bibliographic record
Abstract
According to the idea of some Anthropologists, i.e., Edward Sapir and Benjamin Lee Whorf, Sapir’s student, the unique organization of universe that is embodied in each language might act as a determining fact or in the individual’s habits of perception and of thought, thus forming and maintaining particular tendencies in the associated nonlinguistic culture. The idea provides us with a refreshing angle in understanding one of the important underlying causes for the difference between English and Chinese people in their ways of thinking, and thus induced ways of behavior toward their surroundings and some linguistic light on the historical myth mentioned by the famous British sinologist Joseph Needham and on why Chinese science ceased its development after Middle Ages. Key words: Whorfian hypothesis, language, culture difference Resume: D’apres certains anthrologues comme Edward Sapir et son etudiant, Benjamin Lee Whorf, l’organization unique de l’univers implante dans chaque langage peut etre servie comme un determinant sur l’habititude individuelle d’observation et de la pensee, qui determine et maintient une tendance particuliere dans la culture non-linguistique. L’idee nous permet de comprendre une des raisons implicites des differences dans la pensee entre les chinois et les francais, et induit des mainieres de comportement envers leur environnement et donne une lumiere sur le mythe histoire mentione par le fameux sinologist Joseph Needham et explique pourquoi le developpement de la science chinoise a arrete apres le Moyen age. Mots-Cles: Hypothese de Whorf, langage, difference culturelle
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".