MétaCan
Menu
Back to cohort
Record W4413992238 · doi:10.1080/17441692.2025.2547846

The value of self-care during climate-related extreme weather events (EWE) to support sexual and reproductive health and rights

2025· article· en· W4413992238 on OpenAlexaff
Manjulaa Narasimhan, Carmen H. Logie, Vanessa Brizuela, Andie MacNeil

Bibliographic record

VenueGlobal Public Health · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUnited Nations University Institute for Water, Environment, and HealthWomen's College HospitalUniversity of Toronto
FundersWorld Health Organization
KeywordsSexual and reproductive health and rightsHealth carePreparednessPsychological resilienceGlobal healthReproductive healthPsychological interventionPublic healthEconomic growthPolitical scienceMedicineNursingEnvironmental healthPsychologySocial psychologyReproductive rightsPopulationEconomics

Abstract

fetched live from OpenAlex

Climate-related extreme weather events (EWE) affect sexual and reproductive health and rights (SRHR) outcomes through complex and multi-level pathways. These include institutional-level effects on health systems, such as damaged health infrastructure and roads, barriers to retaining qualified health and care workers, as well as healthcare access barriers due to increased economic precarity, displacement and migration. Furthermore, EWE effects on SRHR disproportionately affect marginalised communities. Optimising SRHR in the context of climate change and EWE thus require moving beyond traditional health system approaches. Self-care interventions (e.g. HIV self-tests) and self-care actions (e.g. self-monitoring blood glucose during pregnancy), whereby affected individuals and communities have increased control and agency over their own health practices, can ensure essential SRHR needs can be maintained during crises. Yet opportunities for SRHR self-care strategies in communities affected by EWE are underexplored. When health systems collapsed during the COVID-19 pandemic in countries spanning income levels, self-care options were prioritised to maintain essential health services. In this commentary, we explore how SRHR self-care interventions and actions can be integrated into EWE emergency preparedness across dimensions of self-management, self-testing, and self-awareness to build individual, community and health systems climate resilience.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.323
Teacher spread0.286 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Public HealthSame topicClimate Change and Health ImpactsFrench-language works237,207