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.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".