Strengthening competition in network sectors and the internal market in Canada
Bibliographic record
Abstract
Canada’s productivity performance has lagged that of many other OECD countries, despite some improvement in recent years. One measure to enhance overall efficiency would be to strengthen competition on the domestic market to drive future multi-factor productivity improvements. The potential gains are large: about a half a percent per year over a fairly long horizon. This paper focuses on increasing competition in network sectors, including energy, telecommunication services and broadcasting, and transportation, which are key inputs to production in the broader economy. Improving regulatory conditions, efficiency and/or cost competitiveness could yield more productive outcomes in these sectors, as well as in downstream industries. Competition could also be increased by lowering barriers to interprovincial trade and the movement of labour, which act to fragment Canada’s already small domestic market. To this end, reforms of the Agreement on Internal Trade and measures to reduce sectoral barriers to trade are also discussed. This Working Paper relates to the 2016 OECD Economic Survey of Canada (www.oecd.org/eco/surveys/economic-survey-canada.htm)
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".