The Economic Performance of Jewish Immigrants to Canada: A Case of Double Jeopardy?*
Bibliographic record
Abstract
This chapter shows that immigrants to Canada who declared themselves in the 1991 census to be religiously “Jewish” display much higher earned incomes as well as much higher values for each and every income-enhancing characteristic than other immigrants display. In Canada the immigration debate reflects several concerns. Research on the economic performance of immigrants to Canada has focused on pertinent characteristics as age, education, marital status, language, entry category, and intended occupation. The chapter discusses the results of testing a human capital model for the Jewish Canadian-born and Jewish immigrant earnings experiences. A human capital model argues that after arrival, Jewish immigrants accumulate, via education, experience and greater language facility, human capital which gradually makes them more competitive in the Canadian labor market. Immigrant Jews share income-enhancing characteristics with the larger population of Jews, with the anomaly that they are relatively less well educated. Jews apparently overcome the “jeopardy” inherent in being immigrants by virtue of other income-correlates.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".