Bibliographic record
Abstract
In 1986, Marcel Kurpershoek, a Dutch diplomat, was posted to Saudi Arabia. There, he started exploring the country's vast deserts and hunting in the Rub 'al-Khali, the Empty Quarter. Three years later, having familiarized himself with the Bedouin dialect and poetry, he set out to do five months of fieldwork among the tribes of central Arabia, travelling the Saudi desert in search of the living chronicle of the Bedouins. He established contacts with tribesmen and Bedouins in this remote corner of the desert and discovered the powerful tribes of Utaybah, Qahtan, Subay and Dawasir, whose poets celebrated bravery and feats of arms. His host, Khalid, a Utaybah Sheikh, told him all he knew of his ancestors' chivalrous feats and daring raids when the tribes were a law unto themselves. He also became the first Westerner to visit ad-Dakhul and Hawmal, two mountains mentioned in Imrul Qais' famous pre-Islamic ode. But his greatest discovery was an old, poor, illiterate and unruly Bedouin, the poet ad-Dindan, whose magnificent poetry offered contemporary proof of the authenticity of the great pre-Islamic tradition in Arabian oral poetry. His encounters are recorded in this part travelogue, part book of poems and study of traditional Saudi society.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".