Bibliographic record
Abstract
From the ruined shell of Rome after the empire’s fall, most of the world Jewish population came under Islamic rule in the seventh and eighth centuries CE. The main influences on Jewish culture, particularly Spanish Hebrew poetry, for the next half millennium were Arabic. Hebrew poetry in Muslim Spain represents a turning point in Jewish life mainly in its non-theological elements, influenced by contemporaneous Arabic poetry with its various genres: love poetry, including homosexual poetry, poetry of friendship, wine songs, war poetry, and so on. 1 This was the most important Hebrew poetry between the end of the biblical age and modern times. Most of it belongs to the narrow period 1031–1140 when the Umayyad empire fell apart and Christian Europe began to overtake Islam, militarily, economically, and culturally. Hebrew poets not only adopted Arabic versification; they seem to some extent also to have been influenced by a secular lifestyle associated mainly with court culture, while at the same time keeping strictly to Jewish tradition and, in fact, also writing poems for the synagogue liturgy. What did the secularization of Hebrew poetry mean? Was it just literary convention, influenced by Islamic poetry? Or did it reflect a lifestyle anticipatory of the modern era? These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".