Bibliographic record
Abstract
Air India Flight 182 exploded over the north Atlantic on June 23, 1985. The majority of passengers and suspects were Canadian citizens, the bombs originated from Vancouver, and the bombing is the worst act of terrorism in Canada’s history. In the immediate aftermath, Canada’s then-Prime Minister, Brian Mulroney, responded by sending condolences to the government of India. Families of the victims subsequently reported “that they felt that they were not viewed as ‘real Canadians’ and that this was somehow not considered to be a Canadian tragedy” (Government of Canada, Commission of Inquiry 2007: 99). This article examines what discourses about the Air India case reveal about Canadian citizenship and conceptions of the Canadian nation. It draws on parliamentary debates, as well as government and Air India Inquiry reports, to demonstrate that the national story woven through the history of the Air India case is a racial one: it erases racism out of its narrative and ultimately imagines Canada and the country’s citizens as white. The article argues that the bombing of Air India was initially constructed as a non-Canadian tragedy involving non-Canadian citizens; hence this event, victims, victims’ families and suspects were discursively distanced from the Canadian nation. However, the events of 9/11 and persistent counternarratives have helped create a climate in which particular concerns expressed by victims’ families have been heard by the Canadian government, and the Air India case has recently been reframed as an act of terror that directly affected Canada, and the victims and surviving families have been embraced as “Canadians.” While unquestionably significant, this shift not only enhances security measures that predominantly and often unjustly target racialized subjects, but it is premised on a colourblind approach that ultimately obscures the central role that systemic racism has played throughout the history of the Air India case.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".