Increasing Canada's International Competitiveness: Is There a Link between Skilled Immigrants and Innovation?
Bibliographic record
Abstract
We use an augmented national ideas production function to examine skilled immigrants' impact on Canadian innovation at the provincial level. Empirically, this model was tested using Canadian data by province on innovation flow over an 11 year time period, where innovation flow is defined in terms of international (U.S.) patents. It was found that skilled immigrants, who are proficient in either English or French, have a significant and positive impact on innovation flow in their home province. Further, in examining skilled immigrants by source region, it was found that skilled immigrants from developed countries have the greatest impact on their home province's innovation flow. This is true of North American/European skilled immigrants for all skill-level categories including language proficiency, education, and immigrant class. For immigrants from developing countries, only highly educated Eastern Europeans and Low Income Asians classified as "Independent Workers" are both significant and positively related to their home province's innovation flow.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".