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Record W4383819602 · doi:10.3390/ijerph20136321

Indigenous Peoples’ Experience and Understanding of Menstrual and Gynecological Health in Australia, Canada and New Zealand: A Scoping Review

2023· review· en· W4383819602 on OpenAlexaboutno aff
Donna Ciccia, Aunty Kerrie Doyle, Cecilia Ng, Mike Armour

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2023
Typereview
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTabooMenstruationPsycINFOGrey literatureReproductive healthPopulationMedicineInclusion (mineral)LiteracyMenarcheGeographySocioeconomicsEnvironmental healthPolitical scienceMEDLINEGender studiesSociology

Abstract

fetched live from OpenAlex

There are a variety of cultural and religious beliefs and customs worldwide related to menstruation, and these often frame discussing periods and any gynecological issues as taboo. While there has been previous research on the impact of these beliefs on menstrual health literacy, this has almost entirely been confined to low- and middle-income countries, with very little information on high-income countries. This project used the Joanna Briggs Institute (JBI) scoping review methodology to systematically map the extent and range of evidence of health literacy of menstruation and gynecological disorders in Indigenous people in the colonized, higher-income countries of Australia, Canada, and New Zealand. PubMed, CINHAL, PsycInfo databases, and the grey literature were searched in March 2022. Five studies from Australia and New Zealand met the inclusion criteria. Only one of the five included studies focused exclusively on menstrual health literacy among the Indigenous population. Despite considerable research on menstrual health globally, studies focusing on understanding the menstrual health practices of the Indigenous populations of Australia, New Zealand, and Canada are severely lacking, and there is little to no information on how Indigenous beliefs of colonized people may differ from the broader society in which they live.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.393
GPT teacher head0.518
Teacher spread0.125 · 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
GenreReview

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

Citations10
Published2023
Admission routes1
Has abstractyes

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