Managing Empire: The Rubber Economy of the Bay of Bengal, 1927-1945
Bibliographic record
Abstract
"Managing Empire: The Rubber Economy of the Bay of Bengal, 1927-1945," follows the reproduction of the British Empire through the rubber plantation complex of India, Ceylon, and Malaya during the Great Depression and Second World War. The Depression shook the foundations of the empire in the Indian Ocean. Collapsing commodity prices threatened millions of pounds of British investment in plantations, stressing an empire financially exhausted by war. With agricultural commodities in freefall, the empire saw mass unemployment, the collapse of inter-Asian commercial and credit markets, the potential transfer of British plantation assets to American investors, and waves of anti-colonial mobilization and communal violence. Drawing on official, business, and press archives in the UK, India, Malaysia, and Singapore, I show how planters, businessmen, statesmen, and colonial officials built a coalition to preserve European command, subject to inter- and intra-class conflict, anti-colonial mobilizations, and militant labour movements. Engaging with the historiography of empire, capitalism, business, and labour in South and Southeast Asia, I argue that the plantation complex was crucial to globalization and fragmentation across empires in the Bay of Bengal.I argue that the rubber economy, including its commodity, capital, and labour markets, was a laboratory for new frameworks of British imperial power, exercised through international economic governance aimed at preserving European command over Asian land, markets, and labour. These experiments in economic diplomacy depended on a professional class of statesmen, civil servants, company directors, and professional managers stretching across colonies, metropoles, and even empires. The rubber economy – its workers, managers, traders, and regulators, both European and Asian – was a pivot point of the empire, depending on negotiations in boardrooms, courts, the press, and on estates. Significant contradictions posed by the drive to preserve European command over Asian economic life resulted in waves of proto nationalization across the Bay of Bengal, emanating from colonial states and militant associational movements of labour unions and anti-colonial nationalists. This interwar experiment of managerial interventions in inter-colonial economic life temporarily protected British capital in the Bay of Bengal while incubating the era of decolonization and partition after the Second World War.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".