An Investigation on Wage Penalties: The Effect of Foreign-Born Status on Employee Wages, Salaries, and Incomes in the United States and Canada
Bibliographic record
Abstract
This paper investigates whether there is a wage penalty that negatively affects foreign-born employees in the United States and Canada, addressing the following two questions: (1) Does being a foreign-born employee result in a wage penalty in the United States and Canada? And if so, (2) How does this penalty differ across the two countries over time? With data collected from the Integrated Public Use Microdata Series (IPUMs), four separate multiple linear regression models are estimated to compare the presence of wage penalties across various industries and occupations. These analyses cover the following comparisons: the United States in 1990 and 2000, Canada in 1991 and 2001, the United States in 1990 and Canada in 1991, and the United States in 2000 and Canada in 2001. For each comparison, this study finds that individuals who identify as foreign-born to the country they are employed, face a wage penalty. These findings indicate that this specific status (foreign-born) correlates to lower wages compared to the average employee and suggests changes in immigration policy in both countries over time as potential explanations. These results are important for future consideration of wage and salary incomes to individuals in both countries, regardless of foreign and domestic-born status.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".