Mixed embeddedness of Brazilian entrepreneurs in Toronto
Bibliographic record
Abstract
Purpose The purpose of this article is to investigate how social integration, immigrant networks and barriers to ventureing affect the entrepreneurial activities of Brazilians in Canada, indicating how mixed embeddedness takes place in that context. Design/methodology/approach Data were collected in Toronto, through the application of a survey with 74 Brazilian entrepreneur respondents and 42 semi-structured interviews with selected subjects, thus representing a multi-method approach. The analysis included descriptive statistics from the survey data and a qualitative analysis of the trajectories and life stories of Brazilian immigrants. Findings Our sample comprises respondents with a high level of education and proficiency in English, coming predominantly from the southeast of Brazil, white, aged from 30 to 49. The majority of businesses are small and related to the service sector. The article contributes to the literature by discussing the elements related to mixed embeddedness, including the need for cultural adaptation and for the creation of networks as a crucial element for business venturing. Research limitations/implications The study focuses on entrepreneurs regardless of their businesses sector or formality/informality status. It could be used as an instrument to support Canadian public policies for welcoming Brazilians and for the Brazilian government to prevent the evasion of potential entrepreneurs. Originality/value The article contributes to the body of knowledge of immigrant entrepreneurship in Canada and of Brazilian entrepreneurship overseas. The results suggest factors that may be relevant to the expansion of their business, such as social networking, cultural embeddedness and adaptation of the products/services to a wider range of target customers.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".