Citizenship, enclaves and earnings : comparing two cool countries
Bibliographic record
Abstract
This paper uses the Canadian 2006 Census and the Swedish 2006 register data to analyse the citizenship effect on the relative earnings of immigrants, using instrumental variable regression to control for citizenship acquisition. We ask: ‘Is there a citizenship effect and if any, in which country is it that we find the largest effect and for which immigrant groups?’ We add one further dimension, asking if the size of the co-immigrant population in the municipality has an effect on earnings. We find that the impact of citizenship acquisition is substantial in both Canada and Sweden. However, the place of birth of immigrants is important. In most cases, immigrant women in Sweden enjoy a higher citizenship premium than is the case for immigrant women in Canada. Amongst men the picture is more mixed. Most European groups receive a larger citizenship premium in Canada as compared to Sweden. Being in a city with more immigrants of the same background is better for earnings in Sweden than in Canada. However, being in a city with a lot of immigrants (regardless of origin) is better in Canada as compared to Sweden.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; both teacher heads agree on what is shown here.
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".