Bibliographic record
Abstract
BARUCH HA'SHEM!I am grateful to have completed this work, first in partial fulfillment of my M.A. thesis in 1980 and now in the voices of these Jewish immigrants.Why did it take so long?It is within the cradle of Jewish Ethics (Mussar) that I have found myself worthy of completing this work.My gratitude abounds for the encouragement and positive feedback I have received from those I have talked to about this book.Twenty-five years ago, few in the publishing business and fewer still in the Jewish community were interested in this work.Times have changed, and with the appearance of another generation, so open and welcoming, came a thirst for Jewish historical data.My heart swells and opens in response.I thank you.It is difficult to begin to acknowledge and give thanks to the many who gave of themselves and who made this work a reality.My expression of gratitude follows neither a chronological methodology nor a meritorious one.Each and every person acknowledged here stands equally tall and needs to be counted.I am forever in your debt.To Penny Goldsmith, for your confidence, for your finding my work praiseworthy, for encouraging me to send my stories to Wilfrid Laurier
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.294 | 0.232 |
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".