Authenticity of Classical Arabic and its relation to Aristotelian Logic (In the opinions of some orientalists and Arab scholars)
Bibliographic record
Abstract
Classical Arabic was originated in the family of Semitic languages as a result of mixing among the languages of thepeople who lived in the Arabian Peninsula. Nobody knows the exact time of its emergence. We had some knowledgeby some stone monuments and oral histories indicated that some distinct languages were in the south and north of theArabian island. Some of their images remained for us that were sometimes seen in some Arabic dialects later in theaspects of their expression, derivation and synonymous words. The age of this classical Arabic is mentioned byal-Jāḥiẓ in his book: “The Animal”, which is between 150-200 years before Islam.There is no doubt that Arabic Language has evolved through the ages and has become a standard language after itwas audible, especially when it established its linguistic bases to protect its originality and Arab nature from themelody entered from the non-Arabs who accepted Islam, after the mixing among Arab Muslims and the other people.It is true that Arabs had used the Aristotelian logic in the development of their linguistic sciences, but their Arabicwas not affected by the Aristotelian logic and their Arab culture did not lose its originality and nature.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".