Is There a Nativity Gap? New Evidence on the Academic Performance of Immigrant Students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Public schools across the United States are educating an increasing number and diversity of immigrant students. Unfortunately, little is known about their performance relative to native-born students and the extent to which the “nativity gap” might be explained by school and demographic characteristics. This article takes a step toward filling that void using data from New York City where 17 percent of elementary and middle school students are immigrants. We explore disparities in performance between foreign-born and native-born students on reading and math tests in three ways—using levels (unadjusted scores), “value-added” scores (adjusted for prior performance), and an education production function. While unadjusted levels and value-added measures often indicate superior performance among immigrants, disparities are substantially explained by student and school characteristics. Further, while the nativity gap differs for students from different world regions, disparities are considerably diminished in fully specified models. We conclude with implications for urban schools in the United States.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it