Diplomatic Tension between India and Canada: Impacts on Migration and Diaspora Politics
Bibliographic record
Abstract
The ongoing diplomatic tensions between India and Canada, triggered by allegations of India's involvement in the assassination of Khalistani activist Hardeep Singh Nijjar, underscore the increasing influence of migration and diaspora politics on foreign policy. The Sikh diaspora in Canada, one of the largest outside India, has played a significant role in shaping Canada's internal and external policies, particularly concerning India. Rooted in historical migration waves during political unrest in India, the Sikh community has achieved political and economic prominence in Canada, influencing its political discourse and foreign relations. While the Khalistan movement has diminished in India, it retains support among certain groups in Canada, leading to referendums and protests that challenge India's sovereignty and fuel diplomatic rifts. Canada's liberal stance on freedom of expression and the Trudeau government?s reliance on Sikh support further complicate matters, reflecting a broader global trend where migration politics impact policy - making. This tension serves as a warning for multicultural societies globally, emphasizing the need for balanced immigration policies and adherence to international norms to foster global harmony, as advocated by former UN Secretary - General Kofi Annan.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.028 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".