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Record W6959880905 · doi:10.13016/dv8u-ku3u

THE WHEELS ON THE BUS FELL OFF: THE RISE AND FALL OF COURT-ORDERED BUSING IN PRINCE GEORGE’S COUNTY, MARYLAND

2025· dissertation· en· W6959880905 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Libraries (University of Maryland) · 2025
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsDesegregationMandateSuburbanizationFellVoter registrationWhite (mutation)PoliticsScholarshipGovernment (linguistics)

Abstract

fetched live from OpenAlex

This study examines the desegregation of Prince George’s County Public Schools and the use of court-ordered busing from 1972 to 1998. As Prince George’s was the only county in Maryland under a federal mandate to integrate, this study explores how residents responded to desegregation and the shifting perceptions of busing over the 25 year period of implementation. After a federal lawsuit in 1972, the county was forced to bus students away from their neighborhood school to ensure every school had a racial balance of black and white students. Perceptions shifted with the shifting demographics driven by black suburbanization and a burgeoning black middle class. Between 1970 and 1990, the county transformed from a sleepy, white, rural county into the wealthiest black-majority county in the United States. After the transformation, the perceptions of court-ordered busing flipped, as many black students were being bused to majority black schools. The new black majority gained political power in the 1990s and took charge of local government to end court-ordered busing themselves. Overall, this study pushes back on previous scholarship that deemed court-ordered busing to be a failed tool of desegregation. It argues that while not perfect in achieving integrated schools, it was a necessary federal intervention for Prince George’s County to dismantle its system of segregation and pursue an equitable education for all students.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.174
Teacher spread0.167 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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