Immigrants Doing Business in a Mid‐sized Canadian City: Challenges, Opportunities, and Local Strategies in Kelowna, British Columbia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Lacking a tradition of settling immigrants and the appropriate infrastructure to integrate them, small‐ and medium‐sized cities often face the challenge of attracting and retaining immigrants. Using a mixed methods approach, this study compares the experiences of immigrant and non‐immigrant entrepreneurs in a mid‐sized C anadian city, K elowna, B ritish C olumbia. A survey reveals different experiences between these two groups, with immigrants facing more challenges. In the absence of institutionally complete communities or strong ethnic economies, immigrants do not rely extensively on their own community resources, an element considered instrumental for immigrant business development in large cities. Compared to non‐immigrants, immigrant entrepreneurs have a more optimistic outlook on doing business in K elowna; this is encouraging for a city trying hard to attract immigrant investment. Key informants recommended transforming the city into a more welcoming community, establishing appropriate support infrastructure, and removing potential institutional offsets. This paper adds new theoretical insights to the literature on immigrant entrepreneurship; all socio‐cultural, political‐institutional, and economic‐structural considerations are embedded in geography. The findings also have implications for growth strategies in small‐ and medium‐sized cities.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it