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Record W3041025275 · doi:10.1080/07352166.2020.1770605

When schools open: Student mobility and racial sorting across new charter schools in Kansas City, Missouri

2020· article· en· W3041025275 on OpenAlex
Patrick Denice, Michael DeArmond, Matthew Carr

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Urban Affairs · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsWestern University
FundersEwing Marion Kauffman Foundation
KeywordsCharterWhite (mutation)Racial compositionSchool choiceCharter schoolSortingRacial differencesPolitical scienceDemographic economicsEconomic growthSociologyPublic administrationGeographyRace (biology)Ethnic groupGender studiesEconomicsLaw

Abstract

fetched live from OpenAlex

Does opening new schools of choice in urban areas lead to increased racial isolation among students? We examine whether the availability of new charter schools in Kansas City, Missouri, shapes patterns of segregation using student-level data between 2012 and 2016. We find that White students are over-represented among those who switch into new charter schools, and that they enter schools with lower proportions of Black students and higher proportions of other White students. This suggests that the sorting of students into new charter schools led to slightly increased levels of racial segregation. But rather than a generalized phenomenon, this sorting appears to be due to two schools with particular characteristics. As cities look to attract more affluent and White families to their urban public schools by opening up new school options, we conclude by discussing how such policies might come at the expense of educational opportunities for lower-income, non-White residents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.365
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it