"Sell” Canada for less: the motives and success for business immigrants and the policy implications
Bibliographic record
Abstract
According to Citizenship and Immigration of Canada, Canada has been competing with the United States, the European Union, Australia, New Zealand and the emerging economics, especially in the Asian Pacific region to attract the limited number of active entrepreneurial talents to Canada, in order to bring in people with business skills and investments. However, business immigrants came under various Canadian immigrant investor schemes that have been underperforming according to recent governmental reports. Policymakers expect newcomers under the investor and entrepreneur scheme to boost Canadian economy, to help Canada integrate into the global economy and assimilate into Canadian society. However, the inferior economic performance of business immigrants indicates that the policy making might have certain limitations and a boundary. Such boundary and limitations are caused by the generalization and lack of understanding of the business immigrant population. Business immigrants emigrate from their home country with different motivations and diverse pre-migration backgrounds (industry, language fluency, local connections to host country, etc). Currently, immigration entrepreneurship research dominantly focuses on the post-migration adaptation and overlooks the pre-migration backgrounds and motives. It is widely identified in the field that the post-migration adaptation and acculturation is correlated to the business immigrants’ pre-migration settings. However, very little research has been conducted in both pre-migration and post-migration settings collectively. In this thesis, I argued that (1) immigration motives and pre-migration backgrounds of business immigrants are critical to predict the success in the post-migration setting; (2) development of four prototypes of business immigrants based on empirical data where the prototypes emerged resulting from in-depth interviews with the local business immigrants in Manitoba; 3) conceptualized dynamic transformation process of business immigrants based on three timelines, namely home country, in transformation and host country.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".