Placed Upon the Landscape, Casting Shadows: Jewish Canadian Monuments and Other Forms of Memory
Bibliographic record
Abstract
This essay explores monuments, including the National Holocaust Monument in Ottawa, and gravestones in Jewish cemeteries in Montreal and Vancouver. Alongside these sites it considers how Canadian Jewish literature presents possibilities for Jewish history and language to mark the Canadian landscape though a consideration of Leonard Cohen and Eli Mandel. A discussion of Canadian monuments is relevant in light of recent demonstrations focused on removing statues and monuments from parks and government buildings. The essay contrasts community-inspired projects like Vancouver’s Holocaust memorial with Ottawa’s “National”monument, whose unveiling prompted a discussion about appropriate ways to represent history.Cet essai explore les monuments, y compris le monument national de l’Holocauste à Ottawa, et les pierres tombales des cimetières juifs de Montréal et de Vancouver. Parallèlement à ces sites, il examine comment la littérature juive canadienne, notamment les écrits de Leonard Cohen et Eli Mandel, offre des opportunités pour l’histoire et la langue juives de marquer le paysage canadien. Une discussion sur les monuments canadiens est pertinente à la lumière des récentes manifestations visant à retirer les statues et les monuments des parcs et des édifices gouvernementaux. L’essai met en contraste des projets d’inspiration communautaire comme le mémorial de l’Holocauste de Vancouver et le monument « national » d’Ottawa, dont le dévoilement a suscité une discussion sur les moyens appropriés de représenter l’histoire.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.033 | 0.026 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".