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Record W3000885236 · doi:10.3368/jhr.1119-10549r5

Investing in Health and Public Safety

2022· article· en· W3000885236 on OpenAlex

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

VenueThe Journal of Human Resources · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsHendrix Genetics (Canada)
Fundersnot available
KeywordsMedicaidPublic health insuranceProperty crimePublic healthMedicineDemographyPsychologyGerontologyHealth insuranceEnvironmental healthViolent crimeCriminologyHealth careEconomic growthEconomicsSociologyNursing

Abstract

fetched live from OpenAlex

<h3>Abstract</h3> A growing body of research documents positive long-term impacts of public health insurance that go far beyond improving recipients’ health. In this study, we expand the analysis to assess whether expanding Medicaid coverage generates reductions in crime. We find that increased Medicaid eligibility during childhood generates significant reductions in crime in early adulthood. Cohorts who experienced expanded Medicaid eligibility during childhood had significantly fewer arrests for property crime, drug-related crime, and driving under the influence in early adulthood. The effects are concentrated among males, are larger for blacks than whites, and larger for eligibility experienced later in childhood.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.098
GPT teacher head0.284
Teacher spread0.187 · 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