“It’s Not Just a Latino Issue”: Policy Recommendations to Better Support a Racially Diverse Population of Undocumented Students
Bibliographic record
Abstract
Even though almost a quarter of undocumented immigrants are not of Latina/o origin, most academic research and institutional support policies have heavily emphasized the experiences and needs of Latina/o undocumented students. This report highlights the experiences of non-Latina/o undocumented college students in an effort to provide insight into how educators, organizers, and interested stakeholders can better support the needs of a racially diverse undocumented student population. We find that the racialization of undocumented immigration as a Latina/o issue differentiates the experiences of Latina/o and non-Latina/o undocumented students by creating disparities in their access to material resources and social support. Building upon these findings, we draw specific policy recommendations that will help better support all undocumented students’ access to and persistence in higher education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".