Transient entrepreneurs?: Chinese migrant small commercial businesses in South Africa
Bibliographic record
Abstract
The influx and establishment of Chinese businesses across Africa have attracted considerable research attention in the last decade, focusing primarily on the larger (state-owned) businesses. By contrast, much less is known about small commercial businesses in terms of their investment motivations, operational conditions, and aspirations of the Chinese business owner-managers in the shopping malls that have emerged to serve such enterprises. This study fills this gap by drawing on interviews with 25 owner-managers of small Chinese shops operating in twelve shopping malls in South Africa. We found that most of them are lightly embedded in the country, due to the competitive nature of their business, language barriers, regulatory uncertainty and crime. At the same time, an inability to extricate themselves and find viable outlets for business elsewhere means that they remain negatively committed. However, a minority of enterprises were much more embedded; we explore the reasons behind this. The study contributes to extending the understanding of small-scale migrant entrepreneurs and embeddedness literature with policy implications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".