Bibliographic record
Abstract
Abstract This article examines the racialized prejudice experienced by individuals from north-eastern India and West Bengal based on their visible, but highly variable, ‘Chinese’ somatic and cultural differences from most of the population. In particular, it isolates a single historical event, the 1962 Sino-Indian War, as a significant moment that coalesced racialized identity in the history of postcolonial India. During and directly after the 1962 conflict, India’s long-standing Chinese community was subject to racist attacks, police harassment, and imprisonment—with over 2,000 individuals, including elderly people and children, being interned for years in a former prisoner-of-war camp in Rajasthan. After being released, many former detainees found it difficult to re-establish their lives and businesses, and many subsequently emigrated to Canada, Australia, Hong Kong, and the United Kingdom. Since the millennium, this ‘forgotten’ history and the traumatic legacy of the racism of 1962 has been the subject of historical novels, memoirs, and community histories. These include Rita Chowdhury’s self-translated historical novel Chinatown Days (2018), Yin Marsh’s memoir Doing Time With Nehru (2015), Joy Ma and Dilip D’Souza’s co-authored non-fiction report The Deoliwallahs (2020), and community-produced video documentaries like The Meridian Society’s The Chinese from Bengal (2011). My article discusses these works as individually and collectively curated attempts to preserve community history and bear witness to the racism and discrimination suffered by members of the community. Citation: Tickell, Alex, ‘Race, the 1962 Sino-Indian Conflict, and India’s Chinese Community’ (20 Mar. 2025), in Paulo de Medeiros, Pablo Mukherjee, and Ranka Primorac (eds), Art and Culture, in Meena Dhanda (ed.), Oxford Intersections: Racism by Context (Oxford, online edn., Oxford Academic, 20 Mar. 2025 -), https://doi.org/10.1093/9780198945246.003.0075, accessed [date].
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".