Differences in Academic Preparedness Do Not Fully Explain Black–White Enrollment Disparities in Advanced High School Coursework
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
Whether racial disparities in enrollment in advanced high school coursework can be attributed to differences in prior academic preparation is a central question in sociological research and education policy. However, previous investigations face methodological limitations, for they compare race-specific enrollment rates of students after adjusting for characteristics only partially related to their academic preparedness for advanced coursework. Informed by a recently-developed statistical technique, we propose and estimate a novel measure of students' academic preparedness and use administrative data from the New York City Department of Education to measure differences in Advanced Placement (AP) mathematics enrollment rates among similarly prepared students of different races. We find that preexisting differences in academic preparation do not fully explain the under-representation of Black students relative to White students in AP mathematics. Our results imply that achieving equal opportunities for AP enrollment not only requires equalizing earlier academic experiences, but also addressing inequities that emerge from coursework placement processes.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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