Unemployment Transitions among Brazilians in the United States and Canada
Bibliographic record
Abstract
Abstract This study uses the job search framework to examine the unemployment experiences of Brazilian immigrants in the North American labour force. Primary data gathered in Canada and the United States is used in these analyses. The model generally used to monitor transitions among the native‐born was modified to make it more appropriate to the immigrant experience. To do this a composite model was constructed that incorporates variables unique to the immigrant experience. Event history analyses revealed that, in general, job search theory is very relevant for examining the transitions of immigrants. However, not all standard measures behaved as predicted (e.g. reservation wage). Several immigrant specific variables were very significant (e.g. target earner and legal status) and improved the overall model fit. Brazilians who worked primarily with other co‐ethnics were more likely to become re‐employed than those who did not, while working for a Brazilian employer had no effect on being re‐employed. US/Canadian comparisons also revealed that residents of Canada endured longer periods of unemployment. We believe this result is because Canadian residents had greater access to public services and, as such, were able to have higher reservation wages.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".