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Record W2167947032 · doi:10.1080/03057070.2011.579433

The Zimba, the Portuguese, and Other Cannibals in Late Sixteenth-century Southeast Africa

2011· article· en· W2167947032 on OpenAlexaff
Eric Allina

Bibliographic record

VenueJournal of Southern African Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCannibalismVernacularPoliticsScholarshipPortugueseMythologyHistoryPower (physics)SociologyMeaning (existential)Gender studiesEthnologyAnthropologyClassicsLiteratureLawPolitical sciencePhilosophyArt

Abstract

fetched live from OpenAlex

This article argues that Portuguese accounts of cannibalism in sixteenth-century southeast Africa reflect important but mostly unrecognised elements of the region's political and cultural history. The article analyses descriptions of the Zimba cannibals in Ethiopia Oriental, written by the Portuguese priest Joo dos Santos. Dos Santos's evidence figures significantly in scholarship for this period, and while many historians include his colourful descriptions of cannibalism, none has taken them seriously, largely dismissing them as a product of European myth-making. In focusing on the question of cannibalism, the article asks not whether the Zimba ate human flesh, nor why they might have, but how dos Santos came to believe that they did. Early modern European cultural outlooks had a role in producing such accounts, but the argument here focuses on how claims of cannibalism reflected African, rather than European, perspectives. Such claims were a vernacular expression of beliefs about, and critiques of, political power in the threatening and unsettled political environment of the time. In transmitting descriptions of cannibalism from African informants, dos Santos acted as an unwitting vehicle for this vernacular critique, conveying its meaning quite imperfectly to his readers.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.277
Teacher spread0.233 · 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
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

Citations8
Published2011
Admission routes1
Has abstractyes

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