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Record W7050685966

Beyond the state

2015· other· en· W7050685966 on OpenAlexfundno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2015
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersJesus College, University of OxfordJesus College, University of CambridgeExecutive Agency for Health and ConsumersUniversity of OxfordBritish Institute in Eastern AfricaUniversity of CambridgeUniversity of Dar es SalaamBritish Medical AssociationYork UniversityWellcome TrustUniversity of Texas at AustinSyracuse UniversityMcMaster UniversityCenter for Agroforestry, University of MissouriWorld Health Organization
KeywordsColonialismEliteGovernment (linguistics)State (computer science)Service (business)Diversity (politics)Health services
DOInot available

Abstract

fetched live from OpenAlex

The Colonial Medical Service was the personnel section of the Colonial Service, employing the doctors who tended to the health of both the colonial staff and the local populations of the British Empire. Although the Service represented the pinnacle of an elite government agency, its reach in practice stretched far beyond the state, with the members of the African service collaborating, formally and informally, with a range of other non-governmental groups. This collection of essays on the Colonial Medical Service of Africa illustrates the diversity and active collaborations to be found in the untidy reality of government medical provision. The authors present important case studies covering former British colonial dependencies in Africa, including Kenya, Malawi, Nigeria, Tanzania, Uganda and Zanzibar. They reveal many new insights into the enactments of colonial policy and the ways in which colonial doctors negotiated the day-to-day reality during the height of imperial rule in Africa.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.981
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.009
Scholarly communication0.0070.004
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0190.002

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 head0.014
GPT teacher head0.276
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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