Examining parental agreement and compliance with recommendations made by a mental health telephone triage service
Bibliographic record
Abstract
Supreme Court cases challenging the Affordable Care Act (ACA) mandate for employer-provided reproductive health care have focused on religiously based opposition to coverage. Little is known about women's perspectives on such reproductive health policies.Data were drawn from the Women's Health Care Experiences and Preferences survey, a randomly selected, nationally representative sample of 1078 US women aged 18–55 years. We examined associations between religious affiliation and attitudes toward employer-provided insurance coverage of contraception and abortion services as well as the exclusion of religious institutions from this coverage. We used chi-square and multivariable logistic regression for analysis.Respondents self-identified as Baptist (18%), Protestant (Other Mainline, 17%), Catholic (17%), Other Christian (20%), Religious, Non-Christian (7%) or No Affiliation (21%). Religious affiliation was associated with proportions of agreement for contraception (p=.03), abortion (p<.01) and religious exclusion (p<.01) policies. In multivariable models, differences in the odds of agreement varied across religious affiliations and frequency of service attendance. For example, compared to non-affiliated women, Baptists and Other Nondenominational Christians (but not Catholics) had lower odds of agreement with employer coverage of contraception (OR 0.63, 95% CI 0.4–0.1 and OR 0.57, CI 0.4–0.9, respectively); women who attended services weekly or more than weekly had lower odds of agreement (OR 0.53, 95% CI 0.3–0.8 and OR 0.33, CI 0.2–0.6, respectively), compared to less frequent attenders.Recent religiously motivated legal challenges to employer-provided reproductive health care coverage may not represent the attitudes of many religious women.Recent challenges to the ACA contraceptive mandate appear to equate religious belief with opposition to employer-sponsored reproductive health coverage, but women's views are more complex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".