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Record W2058090700 · doi:10.5787/35-2-39

CROSSROADS OF WAR: THE PEOPLE OF NKANDLA IN THE ZULU REBELLION OF 1906

2011· article· en· W2058090700 on OpenAlexaboutno aff
Paul Thompson

Bibliographic record

VenueScientia Militaria South African Journal of Military Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSouth African History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsZuluIndigenousHistoryColonialismQuarter (Canadian coin)Government (linguistics)PopulationMonarchySpanish Civil WarAncient historyWhite (mutation)Political scienceResistance (ecology)EthnologyCriminologyLawGender studiesSociologyDemographyPoliticsArchaeology

Abstract

fetched live from OpenAlex

The rebellion and NkandlaThe Zulu Rebellion of 1906 was the violent response to the imposition ofa poll tax of £1 on all adult males (with exempted categories) by the government ofthe British South African colony of Natal on the part of a section of the indigenous,Zulu-speaking people. The rebellion was in the nature of “secondary resistance” toEuropean colonization, and the poll tax was only the immediate cause of it. Not allthe African people (who made up 82% of the colony’s population) participated inthe rebellion; only a few did, but there was the potential for a mass uprising, whichinspired great fear among the European settlers (who made up just 8,3% of thepopulation) and prompted the colony’s responsible government to take quick andvigorous action to crush the rebellion before it could spread. The object of the rebels, beyond the removal of the poll tax, was to drive the white settlers out of thecountry and to restore the pre-colonial regime, although it was unclear just what theythought that might have been. In the case of most (but not all) of the those living inthe Province of Zululand, i.e. the northeastern quarter of the Colony of Natal, itmeant the restoration of the Zulu monarchy under the chief Dinuzulu.

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)0.007
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.281
Teacher spread0.235 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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