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Record W4415889516 · doi:10.1186/s12978-025-02108-9

‘How nice would it be!’: synergies between pro-choice female physicians and abortion acompañantes in Mexico

2025· article· en· W4415889516 on OpenAlexfundno aff
Suzanne Veldhuis, Georgina Sánchez Ramírez, Maribel Campos Muñuzuri, Blair G. Darney

Bibliographic record

VenueReproductive Health · 2025
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
FundersAgencia Estatal de InvestigaciónGrand Challenges Canada
KeywordsAbortionReproductive medicineEmpathyQualitative researchReproductive healthPoliticsPrejudice (legal term)Public healthFocus group

Abstract

fetched live from OpenAlex

Pro-choice female physicians and abortion acompañantes– feminist activists who provide information and accompaniment during self-managed medication abortions– each contribute to safe abortion access in Mexico. Synergistic collaboration between these actors could improve access to safe and high-quality abortion care. We explored the possibility of synergy between pro-choice female physicians and acompañantes in Mexico. This qualitative research is based on feminist epistemology. We used an established framework that describes partner synergy to analyze data from three workshops held with 12 physicians and 13 acompañantes in Chiapas (n = 12), Baja California (n = 9), and Mexico City (n = 4). The workshops sought to foster empathy and reflection on interactions, collaborations, and synergy. Workshop dynamics included sociodrama acting and group discussions. We identified a common interest in building alliances and ideas about synergistic collaborations related to abortion care and accompaniment. Additionally, participants expressed an interest in mutual care arising from the recognition of common experiences of gender-based discrimination and violence among participants, which is a clear expression of synergistic collaboration. Our results also suggest that the pro-choice physicians do not see themselves as political actors, in contrast to the acompañantes, for whom their abortion work is deeply political. We describe that combating prejudice and fostering mutual recognition is necessary for successful collaborations, while the power asymmetry between physicians and acompañantes remains the main barrier to synergy. Finally, we determined that the workshop had an awareness-raising effect that could encourage the creation of subsequent alliances. Creating spaces for meeting and exchange may foster collaborations between these actors from different worlds, which can facilitate access to safe abortions. In Mexico, both pro-choice female doctors and acompañantes—feminist activists who support people through self-managed medication abortions—play important roles in making abortion safer and more accessible. This study looked at how these two groups might work better together. Using a feminist approach, we held three workshops in Chiapas, Baja California, and Mexico City with 12 doctors and 13 acompañantes. The goal was to encourage empathy, understanding, and potential collaboration between them and discuss possible collaborations. We found that both groups were interested in working together to improve abortion care. Participants also recognized shared experiences of gender-based discrimination and violence, which helped build a sense of mutual care and understanding. However, there were also key differences. While acompañantes view their work as deeply political, many doctors did not see themselves that way. Also, power imbalances between doctors and activists remained a major challenge to true collaboration. Despite this, the workshops helped raise awareness and opened the door to future cooperation. Creating spaces for dialogue and connection between these groups may help strengthen alliances and improve access to safe, high-quality abortion care across Mexico.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.372
Teacher spread0.327 · 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.

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
Published2025
Admission routes1
Has abstractyes

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