An Auction Model of Canadian Temporary Immigration for the 21<sup>st</sup> Century
Bibliographic record
Abstract
ABSTRACT Temporary Canadian immigration has grown beyond traditional programs for students, caregivers and agricultural workers to include trade‐related temporary visas under NAFTA and the GATS. Current Canadian debates envision supplanting Canada's permanent immigration programme with a temporary visa programme to remove skill shortages. Several questions emerge under these temporary schemes including who should choose the number of temporary immigrants and under what employment conditions. This paper offers an alternative policy to the current government‐determined quota on temporary visas to answer these two questions. Under the proposed scheme offered in this paper, a Canadian worker can place a job voucher up for auction on the Internet. If the Canadian worker finds an acceptable offer for his one‐year (or less) voucher, then the temporary immigrant is permitted to seek a job in Canada. Thus, under this auction scheme Canadian workers are compensated for the presence of temporary immigrants, and the actual number of temporary immigrants admitted depends on the total number of Canadian workers who sell their vouchers, not on a government fat.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".