Balancing autonomy and collaboration: Acompañantes’ perspectives on health system partnerships for medication abortion care in three Mexican states
Bibliographic record
Abstract
Acompañantes are feminist activists who accompany pregnant individuals through medication abortions outside of clinical settings. This model is safe, holistic, and destigmatizing. In Mexico, where abortion law varies by state and access to public services is limited, self-managed medication abortion with acompañantes is common. This study examines how acompañantes perceive their relationship with the public health system, exploring collaboration opportunities and challenges. We conducted semi-structured interviews with acompañantes from Baja California, Chiapas, and Mexico City—Mexican states with diverse abortion laws, in 2022-2023. The World Health Organization’s Health System Strengthening framework guided the analysis, focusing on stakeholder engagement and innovation. We analyzed the interviews using a qualitative, codebook thematic approach, incorporating both deductive and inductive methods. Seventeen interviews with acompañantes revealed key themes: 1) Acompañantes expressed a tension between operating autonomously and seeing value in collaboration —but not integration— with the formal system for legitimacy, validation, and to improve care experiences for people who access abortion; 2) In a health system where person-centered care is lacking, acompañantes fill this gap and feel a responsibility to do so; and 3) Knowledge gaps, trust issues, and political differences are barriers for acompañantes collaborating with the public health system. Aligning acompañante-supported self-managed abortion with institutional services presents challenges but also opportunities for enhancing care quality and accessibility. Innovative collaborations that respect acompañantes' autonomy and expertise, while addressing systemic barriers, could strengthen health systems and align with WHO guidelines for safe self-managed abortion, including health system referrals if needed or wanted.
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 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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.016 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| 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".