MétaCan
Menu
← Back to cohort
Record W3034719411 · doi:10.2478/eas-2020-0003

Women and Medicine: A Historical and Contemporary Study on Ghana

2019· article· en· W3034719411 on OpenAlexaff
Samuel Adu‐Gyamfi, Kwasi Amakye-Boateng, Ali Yakubu Nyaaba, Adwoa Birago Acheampong, Dennis Baffour Awuah, Richard Oware

Bibliographic record

VenueEthnologia Actualis · 2019
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTabooIndigenousContext (archaeology)Health careGender studiesSociologyMedicineEconomic growthSocioeconomicsGeographyAnthropology

Abstract

fetched live from OpenAlex

Abstract Women have always been central concerning the provision of healthcare. The transitions into the modern world have been very slow for women because of how societies classify women. Starting from lay care, women provided healthcare for their family and sometimes to the members of the community in which they lived. With no formal education, women served as midwives and served in other specialised fields in medicine. They usually treated their fellow women because they saw ‘women’s medicine’ as women’s business. They were discriminated against by the opposite sex and by the church, which regarded it as a taboo to allow women to practice medicine. This study points to a Ghanaian context on how the charismas of women have made them excel in their efforts to provide healthcare for their people. The study also focused on the role of indigenous practitioners who are mostly found in the rural areas and modern practitioners who are mostly found in the peri-urban, urban areas and larger cities in Ghana.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.019
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0080.010
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.047
GPT teacher head0.311
Teacher spread0.264 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEthnologia Actualis→Same topicGlobal Maternal and Child Health→French-language works237,207→