Gender, immigrant status, and unemployment rate sensitivity during recessions
Bibliographic record
Abstract
This study examines the unemployment rates of Canadians comparing men and women, immigrants (any foreign-born Canadians) and native-born to see if there are any groups that are more sensitive than their counterparts during periods of economic downturn (ie.they rise faster than their counterpart group).The results show that neither gender is particularly sensitive although unemployment gaps exist.The gap between native-born and foreign-born is persistent although the results show that it was not especially sensitive during the 2008 global financial crisis.Quarterly data from Statistics Canada was used to run Ordinary Least Squares (OLS) regressions in which the unemployment gaps of each group (men, women and immigrants of both genders) were the dependent variables.The independent variables were GDP, GDP from the industrial sectors which employs the most persons of each group and a dummy variable indicating the appearance of a major recession.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".