Subversive Self-Employment: Intersectionality and Self-Employment Among Dependent Visas Holders in the United States
Bibliographic record
Abstract
Drawing on intersectionality theory, I examine how U.S. visa policies shape the informal self-employment experiences of Indian women and men who migrated to the United States on “dependent visas” to accompany their highly skilled spouses on temporary work visas. Dependent visa policy prohibits employment for the visa holders for a period that can last from 6 to 20 years. Despite this, only a handful of those on dependent visas pursued informal self-employment in my sample, with fewer men than women. This study is based on interviews with 45 participants, with a special focus on 18 dependent spouses (men and women), who had engaged in active self-employment, and tries to understand their experiences with self-employment, particularly their choice of businesses and the role of self-employment in their lives as dependents. I conclude that the complexities of the experiences of self-employment for my research participants are embedded in the intersections of their gender, class, race, and immigration status. Additionally, self-employment itself inadvertently becomes an act of subversion against their state-imposed dependence.
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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 | 0.002 | 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 | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".