Bibliographic record
Abstract
We write the foreword for our fall 2023 volume deep into November, many weeks after the October 7 terrorist attack by Hamas on civilians in Israel.Events have unfolded quickly since then.The story of what led to that moment extend back earlier in time, and the future remains painfully uncertain.At this moment, it feels as though we're at a pivotal point in the history of twenty-first century Jewish life in Israel and around the global diaspora.Jewish Canada is shaken.Time will tell exactly how much will change, and what will remain the same both there and here.For now, we wanted to acknowledge the pain-and the worry, the grief, the anger, the guilt, the incomprehension, the frustration, the shame, and the senses of abandonment, along with the senses of purpose, hopelessness and resoluteness, compassion and anxiety-that have gripped many of those scholars who are a part of the CJS orbit, and the broader Canadian Jewish community we study (and, in many cases, are a part of, intimately).We hope that new and thoughtful scholarship on Jewish life in Canada can serve as a small bit of balm for our aching hearts and strained minds.And, in the fullness of time, we hope that this journal will be able to provide some space for scholarly insight about the ways the unfolding Israel-Hamas war impacts Canadian Jewish life.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.487 | 0.415 |
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".