The Art of Public Mourning: An Introduction
Bibliographic record
Abstract
the air india bombings remain a little-known, little-remembered event in Canadian public memory.Three hundred and twenty-nine passengers were killed by one bomb that detonated on Air India Flight 182 en route to Delhi from Montreal via Toronto on June 23, 1985.Another bomb targeting a second Air India flight the same day caused the deaths of two baggage handlers at the Narita International Airport in Japan.Two years later, writers Clark Blaise and Bharati Mukherjee observed, "the failure to acknowledge the victims of the crash as Canadians remains for most of the families the enduring political grief of Air India 182." 1 Staggeringly, almost twenty-three years later, the Air India Victims' Families Association (aivfa) was still insisting that Canada "failed to incorporate this tragic event into its collective conscience and history." 2 Feeling ignored, abandoned, and even made suspect by their government and many fellowCanadians, the relatives of the dead have struggled for decades in the face of enormous loss and grief to instill a widespread awareness of the events of June 23, 1985, and to bring about something resembling justice.public the "facts" of the Air India narrative as a way of offering "closure to those who still grieve for their loved ones."7 The aim of these efforts would seem to produce, consolidate, and then marshal an official version of the Air India story as a story of Canada's vulnerability to terrorism in order to bolster support for the state's anti-terrorism policy initiatives.This marshalling is not without controversy given how anti-terrorism policies and laws are themselves implicated in perpetuating the very forms of systemic racism that underpin both the bombings and the Canadian government's inadequate treatment of the victims' families in its aftermath.It seems losses experienced by family and friends and their impact on the wider South Asian community in the aftermath of the bombings.Over the past few decades, there have been a significant number of aesthetically based works by artists and writers who have represented these experiences, from Srinivas Krishna's critically acclaimed feature length film, Masala, 10 to Renée Sarojini Saklikar's award-winning book of poetry, children of air india, and By generating conversations between artistic and scholarly works that offer alternative frames for attending to the Air India tragedy, this book refutes the characterization of artistic productions as less reliable than official accounts-a view expressed in the context of the commission of inquiry's hearings.In his summary comments for the first report of the inquiry, 11 Commissioner John C. Major applauds the memorialization of
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".