Why do some employers prefer to interview Matthew but not Samir? New evidence from Toronto, Montreal and Vancouver
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In earlier work (Oreopoulos, 2009), thousands of resumes were sent in response to online job postings across Toronto to investigate why Canadian immigrants struggle in the labor market. The findings suggested significant discrimination by name ethnicity and city of experience. This follow-up study focuses more on better understanding exactly why this type of discrimination occurs -- that is, whether this discrimination can be attributed to underlying concerns about worker productivity or simply prejudice, and whether the behaviour is likely conscious or not. We examine callback rates from sending resumes to online job postings across multiple occupations in Toronto, Montreal, and Vancouver. Substantial differences in callback rates arise again from simply changing an applicant’s name. Combining all three cities, resumes with English-sounding names are 35 percent more likely to receive callbacks than resumes with Indian or Chinese names, remarkably consistent with earlier findings from Oreopoulos (2009) for Toronto in better economic circumstances. If name-based discrimination arises from language and social skill concerns, we should expect to observe less discrimination when 1) including on the resume other attributes related to these skills, such as language proficiency and active extracurricular activities; 2) looking at occupations that depend less on these skills, like computer programming and data entry and 3); listing a name more likely of an applicant born in Canada, like a Western European name compared to a Indian or Chinese name, In all three cases, we do not find these patterns. We then asked recruiters to explain why they believed name discrimination occurs in the labour market. Overwhelmingly, they responded that employers often treat a name as a signal that an applicant may lack critical language or social skills for the job, which contradicts our conclusions from our quantitative analysis. Taken together, the contrasting findings are consistent with a model of ‘subconscious’ statistical discrimination, where employers justify name and immigrant discrimination based on language skill concerns, but incorrectly overemphasize these concerns without taking into account offsetting characteristics listed on the resume. Pressure to avoid bad hires exacerbates these effects, as does the need to review resumes quickly. Masking names when deciding who to interview, while considering better ways discern foreign language ability may help improve immigrants' chances for labour market success.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it