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Record W2616629015 · doi:10.2105/ajph.2017.303763

Effect of the Affordable Care Act on Disparities in Breastfeeding: The Case of Maine

2017· article· en· W2616629015 on OpenAlexaboutno aff
Summer Sherburne Hawkins, Alice Noble, Christopher F. Baum

Bibliographic record

VenueAmerican Journal of Public Health · 2017
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsnot available
FundersBoston College
KeywordsBreastfeedingMedicaidQuarter (Canadian coin)MedicineHealth insurancePrivate insurancePatient Protection and Affordable Care ActHealth careFamily medicineBreast feedingEnvironmental healthDemographyPediatricsEconomic growthEconomicsGeography

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the Affordable Care Act (ACA) breastfeeding provision and test whether changes in coverage affected women differently according to health insurance status. METHODS: We used the All-Payer Claims Database from Maine (2012-2014) to compare health insurance claims for lactation classes and breast pumps between women with private insurance and women with Medicaid (1) before the ACA breastfeeding provision, (2) after the provision came into effect, and (3) after health insurance expansion through the Marketplace. RESULTS: We found limited change in claims for lactation classes over the study period. By contrast, the number of claims for breast pumps among women with private insurance increased from 70 claims in the third quarter of 2012 to 629 claims 1 year later and 803 claims in the third quarter of 2014. Women with Medicaid had only 11 claims for breast pumps over the entire study period. CONCLUSIONS: This 11-fold rise in claims for breast pumps by women with private insurance suggests that these women will likely increase breastfeeding initiation or duration; however, without additional support for women with Medicaid, disparities in breastfeeding may increase.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.362
Teacher spread0.333 · 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 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

Citations12
Published2017
Admission routes1
Has abstractyes

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