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Record W4409831292 · doi:10.1177/00380407251333651

Consequences of Eviction-Led Forced Mobility for School-Age Children in Houston

2025· article· en· W4409831292 on OpenAlexaboutno aff
Peter Hepburn, Danny Grubbs-Donovan, Nicholas Graetz, Olivia Jin, Matthew Desmond

Bibliographic record

VenueSociology of Education · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersChan Zuckerberg InitiativeJPB FoundationEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBill and Melinda Gates Foundation
KeywordsEvictionDisadvantagedQuarter (Canadian coin)RentingDemographyPsychologyDemographic economicsSociologyPolitical scienceEconomicsGeographyLaw

Abstract

fetched live from OpenAlex

Eviction cases are concentrated among renter households with children, yet we know little about the repercussions of evictions for children’s educational trajectories. In this study, we link eviction records in Harris County, Texas, to educational records of students enrolled in the Houston Independent School District between 2002 and 2016. At least 13,000 public school students in Houston lived in households that were filed against for eviction. These students came from disadvantaged backgrounds, and nearly a quarter lived in households that were filed against repeatedly. Students whose parents were threatened with eviction were more likely than their peers to have left the district by the next academic year. Students who remained were more likely to have switched schools, often relocating to schools with fewer resources, more student turnover, and lower test scores. Eviction filings were associated with increases in absences and, among students who switched schools, more suspensions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.464
Teacher spread0.426 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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