INTERPROVINCIAL BARRIERS TO INTERNAL TRADE IN GOODS, SERVICES AND FLOWS OF CAPITAL: POLICY, KNOWLEDGE GAPS AND RESEARCH ISSUES
Bibliographic record
Abstract
This paper summarizes the state of knowledge on internal barriers to trade in goods, services and flows of capital, examines their cost to the economy, and presents some options for addressing the important barriers that remain. A companion paper examines barriers to labour mobility in Canada (Grady and Macmillan, 2007). The paper finds that there is no single overriding research methodology that is most appealing, and suggests employing a methodology most suitable for the use to which the estimates would be put. Researchers could measure the cost of barriers with a case study approach because of its usefulness in focussing attention on specific barriers deserving of attention; update the 1983 and 1995 work of John Whalley, and others; or use computable general equilibrium models to test empirically the gains from increased trade. The study suggests that whether significant progress in dismantling barriers is achieved might well depend on factors such as whether parties abandon or stay with the current Agreement to Internal Trade (AIT) negotiating model. Good progress could also be made with the creation of bilateral and plurilateral agreements such as the Alberta-B.C. Trade, Investment and Labour Mobility Agreement and the recent Interim Agreement on agriculture as it allows like-minded parties to side-step the AIT’s requirement for unanimous consensus. The study also concludes that economic events, such as labour shortages, may well drive the internal trade agenda in the next decade.
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 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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".