Travellers, Merchants and Settlers in the Eastern Mediterranean, 11th-14th Centuries
Bibliographic record
Abstract
This collection of studies (the eighth by David Jacoby) covers a period witnessing intensive geographic mobility across the Mediterranean, illustrated by a growing number of Westerners engaging in pilgrimage, crusade, trading and shipping, or else driven by sheer curiosity. This movement also generated western settlement in the eastern Mediterranean region. A complex encounter of Westerners with eastern Christians and the Muslim world occurred in crusader Acre, the focus of two papers; a major emporium, it was also the scene of fierce rivalry between the Italian maritime powers. The fall of the crusader states in 1291 put an end to western mobility in the Levant and required a restructuring of trade in the region. The next five studies show how economic incentives promoted western settlement in the Byzantine provinces conquered by western forces during the Fourth Crusade and soon after. Venice fulfilled a major function in Latin Constantinople from 1204 to 1261. The city's progressive economic recovery in that period paved the way for its role as transit station furthering western trade and colonization in the Black Sea region. Venice had also a major impact on demographic and economic developments in Euboea, located along the maritime route connecting Italy to Constantinople. On the other hand, military factors drove an army of western mercenaries to establish in central Greece a Catalan state, which survived from 1311 to the 1380s.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".