Toilers across the Seas: Racial Discrimination and Political Assertion among Sikhs in Canada
Bibliographic record
Abstract
New research on the workings of the ‘web of empire’ have revealed that the British Empire was not only sustained by raw materials from India but depended significantly on its manpower working as ‘coolies’, or indentured labourers, in distant plantations in Mauritius, Fiji, West Indies, East and South Africa, and the Straits Settlements. The white dominions of Canada, Australia and the United States (US) similarly depended on low-paid labourers from the East for much of their work of opening up and colonising the prairie wastes. Initially, the bulk of migrants from India in North America came from among the strong and hard-working Sikhs of the Punjab province of India, who found it lucrative to work in these places, lured by the comparatively higher wages than they could obtain at home. However, as the market for labour became saturated by the first decade of the twentieth century, these countries began to erect legal barriers to the free entry of these Indian migrants under pressure from domestic workers, unwilling to face competition from migrants. This came as a great shock to migrant Indians, who had until then been thinking of the empire as a vast field of ‘shared opportunities’. In 1908, Canada tried to exclude Indian migrant labour by legislation, which insisted on ‘continuous passage’ for entering into the ports of the country. This would automatically disable Sikh migrants, who had to change ships to reach Canada. Gurdit Singh’s attempt to charter a Japanese ship, Komagata Maru , in June 1914 to ensure continuous passage for the Sikh migrants to Canada was a challenge to this legal barrier against the migrants. The turning back of this ship from Vancouver shattered the belief of the migrants in an equal imperial citizenship, and it became incendiary material for the revolutionary nationalist propaganda of the Ghadr conspirators, based in San Francisco. Student radicals in Canada and America, such as Lala Har Dayal, Kartar Singh Sarabha, G. D. Kumar and Husain Rahim tried to contact radicals all over the world, in India House in the United Kingdom (UK), France, Egypt, Turkey and Switzerland, and tried to spread their message through journals, like the Ghadr and the Hindustanee from San Francisco and the Al Kasas from Egypt. They even linked their efforts with German imperialist conspirators to gain funding and guidance in their common mission against British imperialism.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.045 | 0.012 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".