Interprovincial Barriers to Labour Mobility in Canada:Policy, Knowledge Gaps and Research Issues
Bibliographic record
Abstract
The purpose of this paper is to identify the most important knowledge gaps on interprovincial barriers to labour mobility in Canada, and to shed some light on potential conceptual, methodological, and data issues associated with research in this area. Consequently, it provides an overview of the current state of play with respect to the most important issues relating to inter-provincial barriers to labour mobility within the Canadian internal market. The three main barriers to labour mobility in Canada, which are considered, are: residency requirements; certain practices regarding occupational licensing, certification and registration; and differences in how occupational qualifications are recognized. These are the main regulatory barriers that are to be removed or reduced under Chapter 7, the Labour Mobility Chapter of the Agreement on Internal Trade (AIT). It also reviews critically the recent relevant research in Canada and in some other jurisdictions (the United States, the European Union and Australia) on barriers to labour mobility. The paper finds that the most important knowledge gap concerns the extent of the regulatory barriers to labour mobility and their impacts and costs. It also concludes that there is nothing fundamentally wrong with the approach of mutual recognition being pursued in Canada to eliminate such regulatory barriers. However, while there has been a fair degree of success in Canada in achieving occupation-specific Mutual Recognition Agreements for occupational qualifications and reconciliation of differences in occupational standards, this progress has been too slow. Moreover, the functioning of the dispute resolution mechanism with respect to\nChapter 7, is overly complex and inaccessible. The dispute resolution mechanism in the Alberta-B.C. Trade, Investment and Labour Mobility Agreement is stronger and simpler than that of the AIT, and definitely one to be considered as a model to improve the AIT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".