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Record W2909595177 · doi:10.1017/s0001972018000918

Creating a ‘monster’: the National Youth Service pre-university training programme, student activism and the Kenyan state, 1978–90

2019· article· en· W2909595177 on OpenAlexafffund
Luke Melchiorre

Bibliographic record

VenueAfrica · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoBritish Institute in Eastern AfricaGovernment of the Republic of Kenya
KeywordsKenyaMonsterMilitantGovernment (linguistics)LoyaltyState (computer science)SociologyPoliticsPolitical sciencePublic relationsPublic administrationLaw

Abstract

fetched live from OpenAlex

Abstract In May 1984, the Kenyan government of Daniel arap Moi introduced a National Youth Service pre-university training programme (NYSPUT) for prospective university students. The programme was designed to instil discipline in Kenyan university students and inculcate them with a sense of loyalty and commitment to the Moi regime prior to their arrival on campus. This article argues that, in practice, however, the scheme had unintended consequences: it served to alienate student recruits from the ruling party and helped radicalize a small but vocal group of student activists, who, when they arrived on campus, confronted the Moi state with some of its most defiant political challenges of the 1980s. Relying on extensive interviews with former student recruits and archival research, this article highlights the key role that the NYSPUT played in shaping Kenya's young generation of 1980s student activists, who represented one of the most united and militant student movements in the country's history.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.618
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.268
Teacher spread0.227 · 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 teacher head, 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

Citations5
Published2019
Admission routes2
Has abstractyes

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