Sharing and Unsharing Memories. Life Stories of Jews from Muslim-Arab Countries: Fear, Anger and Discontent within a Silenced Displacement
Bibliographic record
Abstract
As a massive exodus drained the Jewish communities from Muslim-Arab countries, starting just after World War II a large number of them migrated in cosmopolitan Montréal. This paper offers a new perspective on their displacement, inquiring on individual narratives of their reconstruction of shared and unshared memories. In this post-Shoah and post-colonial migration, how have these departures been represented within individual memory? What are the elements that have been shared and others hidden? And what are the consequences of uprooting within the individual realm?Using an oral history methodology, the life stories of Sephardic Jews reveal a paradigm present in certain individuals of an ever-present fear and emotional burden, as well as an ability to maintain their agency over their own trajectory. Through the sharing of memories enabled by the project Life stories of Montrealers displaced by war, genocide and human rights violation, I will look at four narratives from four individuals that demonstrate these lingering emotions of fear, anger and discontent. By engaging with usually unshared memories, information is revealed on the personal significance of massive displacement and hopeful for future reconciliation with a fragmented past.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".