Development of Aspect and Tense in Semitic Languages: Typological Considerations
Bibliographic record
Abstract
Development of Aspect and Tense in Semitic Languages: Typological Considerations A survey of pertinent literature reveals that many studies of aspect in Semitic languages do not pay a due attention to the crucial theoretical distinction of perfect and perfectivity. In this paper I will adopt the ‘chronogenetic' model of the morphosyntactic development of tense and aspect tested for the Indo-European languages (Hewson & Bubenik 1997) that allows five major aspectual categories to be distinguished (prospective, inceptive, imperfective, perfective, perfect) within ‘Event Time’. I will argue that the appearance in Arabic of the analytic double-finite perfect (of the type kun-tu katab-tu ‘I had written’) was the most significant innovation during the New Stage not to be found in the other Central Semitic languages. During the Middle Stage in Mishnaic Hebrew and Middle Aramaic the canonical progressive aspect was paradigmatized while Classical Arabic created its double-finite counterpart ( kān-a ya-ktub-u ‘he was writing’). The significance of this approach to the study of the universals of tense and aspect will be evaluated.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".