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Record W6958186024 · doi:10.60692/xccj7-yg387

African Indigenous knowledge versus Western science in the Mbeere Mission of Kenya

2023· article· en· W6958186024 on OpenAlexaboutno aff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTraditional knowledgeOpposition (politics)Scope (computer science)Western europe

Abstract

fetched live from OpenAlex

This article sets out to explore the way in which Western science and technology was received in the Mbeere Mission of central Kenya since August 1912 when a medical missionary, Dr T.W.W. Crawford, visited the area. In his dalliance with ecclesiastical matters, Crawford, a highly trained Canadian medical doctor, was sent by the Church Missionary Society (CMS) at Kigari-Embu, in 1910, to pioneer the Anglican mission in the vast area that included Mbeereland, where Mbeere Mission is situated. Contending with the African indigenous knowledge in medicine, environmental conservation, agriculture and other forms of indigenous science, the introduction of Western science and technology, 1912 to 1952, the article argues, did not erase the former; rather, it complimented it. Pockets of general resistance were evident, though Mbeereland, unlike its neighbouring Mutira Mission of 1912, did not offer elaborate opposition to the Western science and technology, partly because the locals could have learnt about it from their neighbours who had experienced it much earlier. Through a historico-narrative design, the research article endeavours to primarily review the coming of Western medicine in Mbeereland: Did it conflict with the African medicine? Methodologically, the data have been collected via archival sources, oral interviews and by reviewing applicable literature.Contribution: The input of this research article to the HTS Journal's vision and scope is seen by appreciating its focus on the interface between African indigenous knowledge and the European science and technology. Although the main focus is

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.016
Scholarly communication0.0040.004
Open science0.0000.003
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 head0.043
GPT teacher head0.230
Teacher spread0.187 · 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.

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
Published2023
Admission routes1
Has abstractyes

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