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Record W2945547945 · doi:10.5539/gjhs.v11n6p193

Views of Male Community Elders With Regards to Medical Male Circumcision at Pfanani Clinic in Limpopo Province, South Africa

2019· article· en· W2945547945 on OpenAlexvenueno aff
Tebogo Maria Mothiba, M Bopape

Bibliographic record

VenueGlobal Journal of Health Science · 2019
Typearticle
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMale circumcisionNonprobability samplingQualitative researchMedicineFamily medicineAdult malePopulationHealth servicesEnvironmental healthSociologySocial science

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the views of male community elders to Medical Male Circumcision at Pfanani clinic in Limpopo Province. A qualitative, descriptive and explorative research design was used. Purposive sampling was used whereby the researchers interviewed a total of 18 male community elders of ages ranging from 40 to 75 years who came for consultation at the Pfanani clinic. Data was collected using semi-structured one to one interviews. Data were analyzed using the Tesch’s open-coding method one theme and its sub-themes emerged. The study found that Medical Male Circumcision is sometimes not a safe procedure, there are several unexpected outcomes which are experienced, Traditional Male Circumcision predispose males to infections, the environment where the Traditional Male Circumcision is done predisposes males to bad environmental conditions, the period when the Traditional Male Circumcision is performed is viewed as a moral teaching session and lessons learned prepares boys for manhood. The study recommended that the Department of Health should conduct workshops and training for traditional circumcisers and train them on how to maintain sterility during circumcision to avoid the initiates not having infection.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.377
Teacher spread0.328 · 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
Published2019
Admission routes1
Has abstractyes

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