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Record W2975859447 · doi:10.20448/801.42.349.357

Young Adults’ Attitudes to Contraception Mediate their Likelihood of Use

2019· article· en· W2975859447 on OpenAlexaff
Kenneth M. Cramer, Emma M. DeRoy

Bibliographic record

VenueAmerican Journal of Social Sciences and Humanities · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBirth controlEthnic groupFamily planningPregnancyAbortionDemographyMarital statusPsychologyAssociation (psychology)MoralityMedicineDevelopmental psychologyPopulationSocial psychologyResearch methodologySociologyPolitical science

Abstract

fetched live from OpenAlex

Whereas 91% of unwed mothers are under 21 years, researchers and health policy advisers hope to unpack the association between a woman’s wish to avoid becoming pregnant and the intention to use birth control, a relation we hypothesized to be mediated by various attitudes to contraceptive use (including cost, ease of use, extra planning, even morality). In total, 22 potential mediators were evaluated using the Relationship Dynamics and Social Life Study – consisting of 1003 Michigan women aged 18-20 years from Caucasian, African, and Hispanic American backgrounds. Results showed a significant relation between avoiding pregnancy and contraceptive use; when divided by ethnic background, the negative association was higher for African Americans compared to Caucasians, and higher still for Hispanics. This relation was mediated by each of: premarital sex is OK if attracted; faster recovery following pregnancy if young; birth control involves too much planning; it’s a hassle to use birth control; and marital relations improve with the advent of children. When divided by ethnicity, we unexpectedly uncovered several suppressor variables, following whose extraction improved the original association. Implications for researchers and health professionals, as well as directions for future research, are outlined.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.304
Teacher spread0.275 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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