Immigrant entrepreneurs’ influence on the career paths of their children
Bibliographic record
Abstract
There is a gap in the research describing how the entrepreneurial spirit of parents who have successfully immigrated can be imprinted onto their children and influence their career paths. The objective of this study is to bridge these two points and examine how these entrepreneurs have guided the career paths of their first-generation children, from the child’s perception. This study aims to benefit society by documenting how first-generation Canadians perceive their parents to have contributed to their future career paths. A survey will be administered to 15 undergraduate students that are born in Canada with at least one parent born outside of Canada that owns and operates a business. The survey assesses each participant on externally validated surveys of entrepreneurial personality aspects (risk aversion, conscientiousness, and openness to experience) to normalize participants on a scale of entrepreneurial orientation. Participants will then be interviewed about their career aspirations, their parent(s’) career(s), expectations from their parent(s), and their parent(s’) encouragement or discouragement of following the same parental career. The principal goal is to develop a theory of entrepreneurial transfer from parent to child that will involve (i) the effect their parents’ journey had on their choices and opinions towards entrepreneurship, (ii) the extent of the child’s desire or lack thereof to follow the career path most approved by their immigrant parents, and (iii) their underlying reasons for the acceptance or rejection of their parents’ desires for their careers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".