Bibliographic record
Abstract
No large city is complete without a bustling array of culturally diverse businesses. Immigrant entrepreneurship rose dramatically in the last decade of the twentieth century and has, inevitably, had a huge impact on urban life. Not only has immigrant business revitalized derelict shopping streets, but it has also introduced 'exotic' products and fostered new forms of social cohesion. In spite of this, we rarely consider how migrants made the trek abroad, what role they play in their country of settlement, and what effect they have on the global economic climate. Through a comparative study of international 'advanced economies', this book explores the impact of immigrant business. It draws on in-depth case studies from Austria, Belgium, France, Germany, Italy, the Netherlands, the United Kingdom, Australia, Canada, the United States and South Africa. Paying specific attention to the particularities of each country, it provides an up-to-date review of theoretical debates that have developed rapidly in recent years. How important is the institutional framework of each country in determining the extent and incidence of immigrant entrepreneurship? What role do welfare systems play in immigration and how do they compare and contrast in different countries? In what ways do immigrants use their own resources, make use of existing ones, and create new ones? Immigrant Entrepreneurs provides a comprehensive, cross-cultural overview of immigrant business in a diverse global economy. Sophisticated in its analysis and innovative in its approach, this timely book is a benchmark publication.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.090 | 0.026 |
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".