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Record W3013447519 · doi:10.2196/16726

A Web-Based Geolocated Directory of Crisis Pregnancy Centers (CPCs) in the United States: Description of CPC Map Methods and Design Features and Analysis of Baseline Data

2019· article· en· W3013447519 on OpenAlexvenueno aff
Andrea Swartzendruber, Danielle Lambert

Bibliographic record

VenueJMIR Public Health and Surveillance · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsDirectoryLegislationBaseline (sea)AbortionGovernment (linguistics)Logistic regressionComputer scienceEnvironmental healthDemographyBusinessMedicineInternet privacyPregnancyPolitical scienceBiologyLaw

Abstract

fetched live from OpenAlex

BACKGROUND: Crisis pregnancy centers (CPCs) are nonprofit organizations that aim to dissuade people considering abortion. The centers frequently advertise in misleading ways and provide inaccurate health information. CPCs in the United States are becoming more medicalized and gaining government funding and support. We created a CPC Map, a Web-based geolocated database of all CPCs currently operating in the United States, to help individuals seeking health services know which centers are CPCs and to facilitate academic research. OBJECTIVE: This study aimed to describe the methods used to develop and maintain the CPC Map and baseline findings regarding the number and distribution of CPCs in the United States. We also examined associations between direct state funding and the number of CPCs and relationships between the number of CPCs and state legislation proposed in 2018-2019 to ban all or most abortions. METHODS: In 2018, we used standard protocols to identify and verify the locations of and services offered by CPCs operating in the United States. The CPC Map was designed to be a publicly accessible, user-friendly searchable database that can be easily updated. We examined the number of CPCs and, using existing data, the ratios of women of reproductive age to CPCs and CPCs to abortion facilities nationally and by region, subregion, and state. We used unadjusted and adjusted negative binomial regression models to examine associations between direct state funding and the number of CPCs. We used unadjusted and adjusted logistic regression models to examine associations between the number of CPCs by state and legislation introduced in 2018-2019 to ban all or most abortions. Adjusted models controlled for the numbers of women of reproductive age and abortion facilities per state. RESULTS: We identified 2527 operating CPCs. Of these, 66.17% (1672/2527) offered limited medical services. Nationally, the ratio of women of reproductive age to CPCs was 29,304:1. The number of CPCs per abortion facility was 3.2. The South and Midwest had the greatest numbers of CPCs. The number of CPCs per state ranged from three (Rhode Island) to 203 (Texas). Direct funding was associated with a greater number of CPCs in unadjusted (coefficient: 0.87, 95% CI 0.51-1.22) and adjusted (coefficient: 0.45, 95% CI 0.33-0.57) analyses. The number of CPCs was associated with the state legislation introduced in 2018-2019 to ban all or most abortions in unadjusted (odds ratio [OR] 1.04, 95% CI 1.01-1.06) and adjusted analyses (OR 1.11, 95% CI 1.04-1.19). CONCLUSIONS: CPCs are located in every state and particularly prevalent in the South and Midwest. Distribution of CPCs in the United States is associated with state funding and extreme proposals to restrict abortion. Researchers should track CPCs over time and examine factors that influence their operations and impact on public health and policy.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.080
GPT teacher head0.382
Teacher spread0.301 · 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

Citations26
Published2019
Admission routes1
Has abstractyes

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