Labour Productivity of Unincorporated Sole Proprietorships and Partnerships: Impact on the Canada-United States Productivity Gap
Bibliographic record
Abstract
This paper asks how the performance of self-employed unincorporated businesses affects the size of the gap in labour productivity between Canada and the United States. To do so, the business sector in each country is divided into unincorporated and corporate businesses, and estimates of labour productivity are generated for each sector. The productivity performance of the unincorporated sector relative to the corporate sector is much lower in Canada than in the United States. As a result, when the unincorporated sector is removed from the estimates for the business sector in each country and only the corporate sectors for the two countries are compared, the gap in the level of productivity between Canada and the United States is reduced. The unincorporated sector consists of both sole proprietorships and partnerships. This paper also investigates the impact of just sole proprietorships on the Canada-United States productivity gap. Sole proprietorships in the two countries more closely resemble one another than do partnerships, as U.S. partnerships are much larger than their Canadian counterparts. When sole proprietorships are removed from the business-sector estimates of each country (allowing a comparison of sole proprietorships to the rest of the business sector, which consists of partnerships and the corporate sector), the gap in labour productivity between Canada and the United States also declines but by only about half as much as when both sole proprietorships and partnerships are removed. The lower productivity of the unincorporated sector (both sole proprietorships and partnerships) accounted for almost the entire productivity gap between Canada and the United States in 1998. Since then, the productivity of the corporate sector in Canada has fallen relative to that of the corporate sector in the United States and the unincorporated sector no longer accounts for the entire gap.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".