MétaCan
Menu
Back to cohort
Record W1494169206

Birth cohort and the black-white achievement gap: The roles of health soon after birth

2009· preprint· en· W1494169206 on OpenAlexaff
Kenneth Y. Chay, Jonathan Guryan, Bhashkar Mazumder

Bibliographic record

VenueEconstor (Econstor) · 2009
Typepreprint
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsBooth University College
Fundersnot available
KeywordsDemographyCohortConvergence (economics)MedicineCohort effectCohort studyInfant mortalityGerontologyPopulationEconomicsSociology
DOInot available

Abstract

fetched live from OpenAlex

One literature documents a significant, black-white gap in average test scores, while another finds a substantial narrowing of the gap during the 1980's, and stagnation in convergence after. We use two data sources - the Long Term Trends NAEP and AFQT scores for the universe of applicants to the U.S. military between 1976 and 1991 - to show: 1) the 1980's convergence is due to relative improvements across successive cohorts of blacks born between 1963 and the early 1970's and not a secular narrowing in the gap over time; and 2) the across-cohort gains were concentrated among blacks in the South. We then demonstrate that the timing and variation across states in the AFQT convergence closely tracks racial convergence in measures of health and hospital access in the years immediately following birth. We show that the AFQT convergence is highly correlated with post-neonatal mortality rates and not with neonatal mortality and low birth weight rates, and that this result cannot be explained by schooling desegregation and changes in family background. We conclude that investments in health through increased access at very early ages have large, long-term effects on achievement, and that the integration of hospitals during the 1960's affected the test performance of black teenagers in the 1980's.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueEconstor (Econstor)Same topicUrban, Neighborhood, and Segregation StudiesFrench-language works237,207