Global Entrepreneurship Monitor (Gem) - 2001 Canadian National Executive Report
Bibliographic record
Abstract
In 2001, 7% of all adults in Canada were actively engaged in starting a business. In this respect, Canada ranked 14th of the 29 countries participating in the Global Entrepreneurship Monitor (GEM) research project in 2001. Three investigation methods are used in the GEM studies: an adult population survey; interviews with entrepreneurship experts in that country; and selected national and demographic data.The GEM model examines general framework conditions for economic growth and nine entrepreneurial framework conditions – financial support, government policy, government programs, education and training, research and development transfer, commercial and professional infrastructure, market openness, access to physical infrastructure and cultural and social norms. Among the findings: The activity rate for Canadian women entrepreneurs was 63.4% of Canadian men in 2001; this represents a change from 2000, when Canadian women entrepreneurs ranked not significantly behind men. Of the adult population, 3.8% invests directly in new business startups. In terms of informal (angel) and venture capital per capita, Canada ranked 7th of 14 GEM countries reporting in 2001. Of the total capital available, the amount of informal capital available ranked the lowest of the 14 countries. Significant progress is being made in the entrepreneurial environment faced by small and medium enterprises (SMEs) in Canada in the following areas: corporate taxes, capital gains taxes, rollovers of capital gains in SME investments, etc. The most important areas for improvement are in cultural and social norms, financial support, taxation and regulation, and entrepreneurship education.(CBS)
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".