Giving the Devil His Diu: Malik Ayyaz, the Estado da India and Reassessing Comparative Naval Power in the Early Modern Indian Ocean
Bibliographic record
Abstract
The 1509 Battle of Diu is regularly cited as a definitive example of European naval superiority over the Asian powers of the Indian Ocean. Some authors, like the late Jan Glete, have gone so far as to assert that, after Diu, no Indian Ocean state was ever able to challenge the Portuguese at sea again. Yet these analyses ignore that Portugal’s primary adversary in India, Gujarati governor Malik Ayyaz, not only survived the battle of Diu but also continued to wage a private war against the Estado da India until shortly before his death in 1522. This article examines Ayyaz’s war against Portugal from beginning to end and uses his career as a lens through which to offer a re-evaluation of Gujarati naval strength in the early sixteenth century. Its findings suggest that the conflict between Ayyaz and the Estado da India was ultimately a draw, with neither side possessing a meaningful technological or military advantage over the other.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".