Access to Contraceptive Services in Puerto Rico: An Analysis of Policy and Practice Change Strategies, 2015-2018
Bibliographic record
Abstract
CONTEXT: During the 2016-2017 Zika virus outbreak in Puerto Rico, preventing unintended pregnancy was a primary strategy to reduce Zika-related adverse birth outcomes. The Zika Contraception Access Network (Z-CAN) was a short-term emergency response intervention that used contraception to prevent unintended pregnancy among women who chose to delay or avoid pregnancy. OBJECTIVE: This analysis reports on the identified policy and practice change strategies to increase access to or provision of contraceptive services in Puerto Rico between 2015 and 2018. METHODS: A policy review was conducted to document federal- and territorial-level programs with contraceptive coverage and payment policies in Puerto Rico and to identify policy and practice change. Semistructured interviews with key stakeholders in Puerto Rico were also conducted to understand perceptions of policy and practice change efforts following the Zika virus outbreak, including emergency response, local, and policy efforts to improve contraception access in Puerto Rico. RESULTS: Publicly available information on federal and territorial programs with policies that facilitate access, delivery, and utilization of contraceptive coverage and family planning services in Puerto Rico to support contraceptive access was documented; however, interview results indicated that the implementation of the policies was often limited by barriers and that policy and practice changes as the result of the Zika virus outbreak were short-term. CONCLUSION: Consideration of long-term policy and practice changes related to contraceptive access is warranted. Similar analyses can be used to identify policies, practices, and perceptions in other settings in which the goal is to increase access to contraception or reduce unintended pregnancy.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".