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Record W4411867261 · doi:10.1371/journal.pone.0310878

The practice of gender and protection mainstreaming in health response in humanitarian crisis - A case study from the refugee camps in Cox’s Bazar, Bangladesh

2025· article· en· W4411867261 on OpenAlexaff
Charls Erik Halder, Md Abeed Hasan

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsThematic analysisGender mainstreamingMainstreamingRefugeePreparednessMedicinePsychological interventionQualitative researchPsychologyPolitical scienceNursingSociologySocial scienceSpecial education

Abstract

fetched live from OpenAlex

BACKGROUND: The health system is required to be safe, equitable, and accessible to all ages, gender, and vulnerable groups, including older persons and persons with disability, and address their specific needs and concerns. However, limited evidence is available on the effectiveness and practicality of gender and protection mainstreaming interventions in health response in humanitarian crises. OBJECTIVE: The overall objective of the research was to explore practices, gaps, and challenges and generate recommendations regarding gender and protection mainstreaming in health response to the Rohingya refugee crisis in Cox's Bazar, Bangladesh. METHODOLOGY: The research employed a qualitative case study design to explore the practice of gender and protection mainstreaming in health response in Cox's Bazar. Data collection methods include an extensive literature review and in-depth interviews with professionals. The professionals interviewed from the area of health and protection, specifically gender, child protection, emergency health intervention, and primary health activities. Data were analyzed using thematic analysis related to gender and protection mainstreaming. Limitations were assessed as to researcher bias because the researcher did all the coding; however, an open recording process, inter-literature cross-potentiation, and ethical considerations of research helped add to the reliability of the research. Exclusion criteria were defined to ensure data consistency, removing insufficiently detailed responses not pertinent to the research objectives. RESULT: The study found a range of good practices on gender and protection mainstreaming in health response, e.g., placement of a gender action plan, monitoring system for gender and disability inclusion, emergency preparedness and response system, availability of sex-segregated toilets and waiting spaces, availability of gender-based violence service and engagement of female community health workers. The study also revealed some best practices which have the potential to scale up, e,g. psychosocial spaces at health facilities for children, palliative care for terminally ill patients, integrated medical and protection services, and facilitation of community health facility support groups. Critical gaps were found in the areas of women's leadership, coordination, capacity building, targeted interventions for vulnerable groups, infrastructural adaptation and consultation with the community on their concerns. CONCLUSION: We urge policymakers, sector coordinators, health program management, healthcare workers, and global stakeholders to address the gaps and challenges, learn and scale up the best practices, and take action to implement the study's recommendations to maximise gender and protection mainstreaming in health response.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0210.015
Scholarly communication0.0050.004
Open science0.0030.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.065
GPT teacher head0.349
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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