Low-technology industries and the skill composition of immigration
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
Abstract This paper examines the relationship between the industry mix and policy decisions regarding the skill composition of immigration. I start with the premise that low- and high-technology industries are unequally affected by changes in the intensity of factors of production, and develop conflicting preferences over immigration policies. To avoid the negative reactions that would ensue from the depletion of regional industries, governments have incentives to adjust the skill composition of immigration in order to maintain the existing regional industry mix. I test the implications of this argument using data on Canadian provinces between 2001 and 2010, and a research design based on the two-stage least squares methodology. Overall, the empirical results are consistent with the theory: provinces relying intensively upon low-technology industries are likely to receive higher proportions of low-skilled immigrants. A consequence is that immigration policies may sustain existing technological gaps between regions and temper down the growth of high-technology sectors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it