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Africa Must Be Modern: A Manifesto

2019· article· en· W4288940130 on OpenAlexaffabout
Andrew Kettler

Bibliographic record

VenueJournal of West African History · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsManifestoIconCitationPublishingDownloadState (computer science)Library scienceHistoryWorld Wide WebComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Book Review| March 01 2019 Africa Must Be Modern: A Manifesto Africa Must Be Modern: A Manifesto, Olúfémi Táíwò, Bloomington: Indiana University Press, 2014, pp. 256, $25.00 paper. Andrew Kettler Andrew Kettler University of Toronto Search for other works by this author on: This Site Google Journal of West African History (2019) 5 (1): 143–145. https://doi.org/10.14321/jwestafrihist.5.1.0143 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Andrew Kettler; Africa Must Be Modern: A Manifesto. Journal of West African History 1 March 2019; 5 (1): 143–145. doi: https://doi.org/10.14321/jwestafrihist.5.1.0143 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveMichigan State University PressJournal of West African History Search Advanced Search The text of this article is only available as a PDF. Copyright © 2019 Michigan State University. All Rights Reserved2019 Article PDF first page preview Close Modal You do not currently have access to this content.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.002
Scholarly communication0.0070.005
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0200.006

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 head0.032
GPT teacher head0.246
Teacher spread0.215 · 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 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

Citations1
Published2019
Admission routes2
Has abstractyes

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