Memory and citizenship in diaspora: remembering the Armenian Genocide in Canada
Bibliographic record
Abstract
This article explores how two public commemorations, the ‘March for Unity’ in Toronto and the ‘Thank you Canada!’ rally in Ottawa, have remembered the Armenian Genocide. Drawing on a qualitative analysis of field notes, speeches, and symbols, it argues that these mnemonic events illustrate the transnationalization of the Armenian Genocide around the overarching theme ‘I Remember and Demand.’ At the same time, these mnemonic events reveal the ways in which transnational memories of the Armenian Genocide are rearticulated in Canada through the prevailing narratives of memory and citizenship. Overall, these commemorations demonstrate that memory is central not only to the construction of Armenian ethnic identity within the constituents of ‘the Armenian Centennial Committee of Canada,’ the organizer of both events, but also to these groups’ and actors’ interpretations and practices of citizenship such as claims-making and public visibility.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.023 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".