Bibliographic record
Abstract
FINALIST for the J.I. Segal Prize, Jewish Public Library, Montreal, 2024 An eye-opening account of the Jewish immigration experience in the 1930s, and one man’s battle against anti-Semitic immigration policies. In 1930, a young Jewish man, Yehuda Yosef Eisenstein, arrived in Canada from Poland to escape persecution and the rise of Nazism in the hopes of starting a new life for himself and his family. Like countless others who made this journey from “non-preferred” countries, Eisenstein was only granted entry because he claimed to be single, starting his new life with a lie. He trusted that his wife and children would be able to follow after he had gained legal entry and found work. For years, he was given two choices: remain in North America alone, or return home to Poland to be with his family. Born from years of archival research, Who Gets In is author Norman Ravvin’s deeply personal family memoir, telling the story of his grandfather’s resolute struggle against xenophobic and anti-Semitic government policies. Ravvin also provides a shocking exposé of the true character of nation-building in Canada and directly challenges its reputation as a benevolent, tolerant, and multicultural country.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.461 | 0.304 |
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".