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Record W7029056518

The Impact of Adverse Childhood Experiences and Allostatic Load on Premature Birth Rates: A Literature Review

2024· article· en· W7029056518 on OpenAlexaboutno aff

Bibliographic record

VenueUSF Scholarship Repository (University of San Francisco) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCommunism, Protests, Social Movements
Canadian institutionsnot available
Fundersnot available
KeywordsAllostatic loadAllostasisRacismAdverse Childhood ExperiencesPremature birthPublic healthPsychological stress
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the relationship between Adverse Childhood Experiences (ACEs), allostatic load, and the likelihood of women giving birth prematurely in the United States and Canada. I searched multiple databases exploring this association, identifying nineteen articles published between 2004 and 2024. The literature highlights that racism and discrimination are a cause of chronic stress, and that this stress, and implicit bias, are both implicated in preterm birth. While ACEs scores have been found to be associated with preterm birth, the results for allostatic load are mixed. The results suggest that more attention should be paid to mitigating the stress associated with racism among pregnant women. One recommendation that has proven successful is for women to have a doula while pregnant, during labor, and postpartum, to educate, support, and advocate for them.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.290
Teacher spread0.278 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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