Bibliographic record
Abstract
The Ghadar movement stood for the revolutionary overthrow of the British rule in India. It had two pronged strategy: to expose the racial discrimination of the American, Canadian and the British Government towards Indians and to evoke national pride for independence of India. Those who worked for it were Punjabi immigrants, mostly Sikhs, small and middle peasants at home, working as labourers in farms and factories in the U.S.A. and Canada. Their emigration was a response to economic frustration and oppression at home. In the foreign land, they were treated as slave. They faced racial discrimination there and treated badly in respect of housing and payment. In America, colour prejudice grew against them. This treatment developed feelings of hatred and repulsion among them and they started organizing themselves into some societies. A small number of educated revolutionaries played a significant role both in the evolution of the movement and direction given to it. Most important ideologue among them was Lala Hardayal. His interaction with the Indian emigrants aroused in him visions of organizing a mass revolutionary movement. He became the guiding force for the Indians, living in North America and gave direction to the already developing movement among the immigrants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".