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Record W4400988761 · doi:10.5430/jnep.v14n11p35

“What are we doing here?”: Reflections on developing a transcultural “Road Map” for global menstrual hygiene management

2024· article· en· W4400988761 on OpenAlexaffvenue
Jodie Bigalky, April Mackey, Annie Namathanga, Pammla Petrucka

Bibliographic record

VenueJournal of Nursing Education and Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNarrativeMenstruationContext (archaeology)PsychologyNarrative inquiryExperiential learningMedical educationMedicineNursingPedagogyGeographyArt

Abstract

fetched live from OpenAlex

Introduction: Globally, reproductive aged girls and women experience personal and social barriers to access the simplest of supplies or menstrual friendly hygiene facilities, exclusion from full participation, and even violation of their human rights, simply because they are experiencing the biological event of menstruation. In Malawi, Africa specifically, the management of menstruation is a challenge for girls and women. This paper examines the process of developing a menstrual hygiene friendly facilities tool for the Malawian context.Methods: Autobiographical narrative inquiry was used for this research. Chronological annals, personal communications, draft tool development documents, journals, text messages, photos, and mementos were used to co-construct an experiential narrative.Results: Four threads that shaped the process of this nursing research collaboration were identified through the creation of the narrative as follows: (1) feeling vulnerable, (2) our realization, (3) building collaborative relationships, and (4) revisiting the product of the research.Conclusions: Three implications for global transcultural nursing practice emerged from this research: (1) collaborative partnerships, (2) cultural adaptions of interventions, and (3) continuous learning and reflection. These implications can be used to guide future international nursing research.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.166
GPT teacher head0.520
Teacher spread0.354 · 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 designOther design
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
Published2024
Admission routes2
Has abstractyes

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