Examining the Canadian Sociocultural Model of Entrepreneurship and Acculturation of Immigrant Entrepreneurs in Saskatchewan
Bibliographic record
Abstract
Each year, thousands of immigrants come to Canada seeking a better life, with many pursuing entrepreneurship. These immigrant-owned businesses contribute significantly to the nation’s prosperity. Supporting them effectively requires understanding how they adapt to a new entrepreneurial culture. This project explored the acculturation of immigrant entrepreneurs in Canada using the Theory of Sociocultural Models (TSCM; Chirkov, 2020a, 2020b). TSCM views acculturation as the process of navigating differences between the sociocultural models (SCMs) of one’s home and host countries. In business, this involves adapting to culturally rooted values, beliefs, and practices. Immigrant entrepreneurs bring internalized SCMs from their countries of origin, which may clash with Canada’s entrepreneurial norms. The first phase of the project explored Canada’s sociocultural model of entrepreneurship (SCMofE) through a scoping review of existing research. This review aimed to identify the public aspects of communally shared models that shape the environment immigrant entrepreneurs must navigate. The Canadian SCMofE reflects individualist values and a commitment to diversity and inclusion, characterized by a dual discourse: it promotes innovation, initiative, and community contribution while also expressing cultural ambivalence toward entrepreneurial risk-taking and fear of failure. Communication norms vary between Francophone and Anglophone communities. In communication, entrepreneurs emphasize self-expression, diplomacy, and a non-confrontational style of interaction. Institutionally, entrepreneurship is shaped by a centralized, formal regulatory system that reinforces compliance and inclusivity. Key practices include reliance on mentors, investors, and both formal and informal networks, though informal regulation remains underexplored. This study provided foundational insights into the distinctive Canadian SCMofE that regulates entrepreneurial behaviour. The second study analyzed data from Statistics Canada’s 2017–2018 Canadian Community Health Survey to assess acculturation stress among immigrant entrepreneurs. Using ANOVAs, it compared psychological and social well-being between immigrant and Canadian-born self-employed individuals. Immigrants reported better perceived mental health but lower life satisfaction and social support. Gender and racial differences also emerged: men reported better mental health in relation to women, while women reported higher social support. Although the large sample revealed sociocultural challenges for immigrant entrepreneurs, the analysis was unable to uncover the underlying mechanisms behind these issues. To explore underlying mechanisms, in Study 3, I interviewed seven immigrant women entrepreneurs with diverse backgrounds (70% from Asia). All recognized tensions between their home countries and Canada’s SCMofE. They engaged in two acculturation processes: one involved practical business actions, such as attending local events, seeking mentorship, joining training programs, and launching businesses. The other was internal, involving self-reflection on differing norms and values. Through these processes, each woman gradually developed new mental frameworks, adapted to her business approach. Successful acculturation involved recognizing SCMofE differences, transforming the self, and building autonomous agency to adopt a new entrepreneurial model. The mechanisms of acculturation identified cognitive, emotional and behavioural processes: interacting with new communities while reflecting on observed differences. The emerged agency of entrepreneurs was at the center of this navigation. In conclusion, this project makes an important theoretical and practical contribution by offering a refined definition of entrepreneurial acculturation grounded in TSCM, along with a theory that highlights the mechanisms and dynamics of acculturation in immigrant entrepreneurship.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".