Bibliographic record
Abstract
I feel singularly privileged to write the introduction for the first of two special JIOWS festschrift editions honouring Michael Pearson’s contributions in the field of Indian Ocean studies. My association with Mike goes back to 1979/80 when I met him at the University of Viswabharati, where my mentor Ashin Dasgupta was working with him on an edited volume devoted to the history of India and the Indian Ocean. This was a time when as a young graduate student, I was being exposed to the hotly debated and discussed sub-field of maritime history. Several senior historians questioned the need to study maritime history outside the general frame of Indian economic history, by then an established field of enquiry, driven primarily by the agrarian question, poverty and the drain of wealth paradigm. I recall how, in course of my apprenticeship, I read a range of writings that looked at Asian trade and commercial exchanges that, although written largely out of European archives, dared to tell a very different story to the dominant one of European commercial and military hegemony. This was long before the heady debates of globalization, of Asia before Europe or indeed of the world system thesis that had entered the field; instead, we were chewing over the critiques of the peddler thesis put forward by Van Leur, and of the uncritical endorsement of colonial perspectives on Asian trade embodied in the writings of scholar administrator W.H. Moreland. It was here that Pearson and Dasgupta gave us the vital tools of our trade, to look beyond the official voices in the archive, to search for private adjustments and compromises that had so much more to say about the messy world of commercial and social transactions where to look for Weberian rationality or pure economic determinism was chasing a mirage.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.061 | 0.016 |
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".