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Slavery in the Mandara Mountains and Lake Chad Basin

2024· reference-entry· en· W4392953189 on OpenAlexaff
Melchisedek Chétima

Bibliographic record

VenueOxford Research Encyclopedia of African History · 2024
Typereference-entry
Languageen
FieldSocial Sciences
TopicEurasian Exchange Networks
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsStructural basinGeographyGeologyPhysical geographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract The demand for slaves in the Lake Chad Basin spanning a long period from at least the 16th century through the first half of the 20th century significantly shaped the physical and human landscapes. Throughout this long period, the Mandara Mountains were part of the practice of slavery as an area of predation first for Kanem-Borno between the 15th and 18th centuries and then for the kingdom of Wandala since the 18th century and the Sokoto Caliphate through the Lamidate of Madagali since the 19th century. To better contextualize the issue of slavery and its role in the political and social transformations of the Chadian Basin, we will rely on three types of sources: first, the travel reports of European explorers and the German, French, and English colonial archives which reported the practice of slavery in the region; second, oral traditions collected by historians and anthropologists; and third, a diary dictated between 1912 and 1927 by Hamman Yaji, the most important slave raider in the southern Lake Chad Basin during that period. As an internal source dating back to the beginning of the 20th century, this diary provides insight into the explosion of slave raids in the early years of colonial occupation and offers unique insight into the relationship between slave-owning and enslaved societies as well as the ambiguous relationship between colonial masters and slave-owning societies.

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)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.066
GPT teacher head0.347
Teacher spread0.281 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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