Immigrant Entrepreneurship: A Survey of "Start-Up" & Investor Via Programs and their Effects
Bibliographic record
Abstract
Entrepreneurship has positive economic benefits and allows for innovative progress within countries. Immigrants, specifically, are in a unique position to bring new perspectives, backgrounds, and ideas to their host countries, which makes them especially entrepreneurial. In particular, immigrants play key roles in their host country by starting businesses or making investments that lead to job creation, innovation, and increased national productivity. This broader phenomenon is known as Immigrant Entrepreneurship, where immigrants contribute to the economy of their host country by starting new businesses or investing. Immigrant entrepreneurship is a developing but relevant topic, as literature in this arena suggests that the rate of business ownership among foreign-born individuals is higher than that of native-born individuals in developed countries. There are two types of visa programs that are particularly relevant to immigrant entrepreneurship: start-up visa programs and immigrant investor visa programs. Recently, against the backdrop of competing economies and the rapid growth of new industries, countries have enacted start-up visa programs to attract talented and innovative immigrants. The goal of start-up visa programs is usually to attract immigrant entrepreneurs to set up “innovative high potential businesses.” Immigrant investor visa programs, on the other hand, offer paths to residency in a foreign country on the condition that a significant financial investment or transaction has been made. These visa programs have become increasingly common within the last two decades, but only certain financial investments apply, and the investment requirements depend on the visa program. With these kinds of visa programs becoming more common in order to promote national economies in a competitive global landscape, this case note will examine the start-up and investor visa programs of three countries and study the success of those programs in terms of increasing minority representation, accessibility, and influence on minority and immigrant-owned businesses. Accordingly, this paper is broken into six main parts. First, this paper will provide general insight into the history and development of these visa programs, as well as study the recent trends surrounding these visa programs. Second, this paper will discuss the current state of immigrant entrepreneurship and what preliminary effects they are producing. The next three sections will be an overview of individual start-up or investor visa programs, examining the United States (U.S.) EB-5 Investor Visa Program, Canada Start-up Visa Program, and the United Kingdom (UK) Innovator Founder Visa. Finally, this paper will survey the practical results of these visa programs in terms of minority representation and how the programs may influence immigrants on whether to engage in a start-up venture.
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.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".