Bibliographic record
Abstract
There are many different opinions on the arbitrariness of linguistic signs. This paper will review these different understandings of the arbitrariness and linguistic signs and some arguments of some famous linguists over the arbitrariness of linguistic signs. Although now we can not gain a final solution to these arguments, we can see that these arguments themselves are developing, improving and that they improve the theory of arbitrariness of linguistic signs as a whole. Holding a developing and philosophical attitude to the arbitrariness of linguistic signs, we can say that while the connection of sound to concept may have been arbitrary, the relationships between linguistic signs after they are made within a language system are not arbitrary. Key words: arbitrariness; linguistic signs; comprehensive view Resume: Il y a beaucoup d'opinions differentes sur le caractere arbitraire des signes linguistiques. Cet article passera en revue quelques conceptions differentes et des arguments de certains linguistes celebres sur le caractere arbitraire des signes linguistiques. Bien que nous ne pouvons pas avoir une solution definitive a ces arguments, nous pouvons constater que ces arguments sont eux-memes en cours de se developper et s’ameliorer et qu’ils ameliorent la theorie de l'arbitraire des signes linguistiques dans son ensemble. En tenant une attitude philosophique en developpement a l’egard de l'arbitraire des signes linguistiques, nous pouvons dire que bien que la connexion du son au concept pouvait etre arbitraire, les relations entre les signes linguistiques apres leur creation dans un systeme linguistique ne sont pas arbitraires. Mots-cles: arbitraire; signes linguistiques; opinion globale
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.057 |
| Scholarly communication | 0.012 | 0.023 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".