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Record W4387762437 · doi:10.1017/9781009296441.003

Introduction

2023· book-chapter· en· W4387762437 on OpenAlexaboutno aff
Bernard Μοitt

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
Fundersnot available
KeywordsLegal guardianColonialismPolitical scienceHistoriographyKinshipLawGender studiesSociologyHistoryEthnology

Abstract

fetched live from OpenAlex

The introduction outlines the scope and parameters of the study and evaluates the historiography of child servitude in Senegal while pointing to the daunting challenges that researchers face in tackling this subject due to fragmented and spotty data. It begins by explaining the meaning of tutelle – a system of guardianship or wardship that emerged after 1848 when slavery ended in the French colonial empire. It associates guardianship with slavery and other forms of coercive labor systems such as engagement à temps or indentureship to which enslaved people, including children, were often subjected through the process of rachat or ransom from slavery. It posits that guardianship in Senegal was institutionalized servitude sanctioned by the colonial administration which spearheaded the distribution of liberated and orphaned children, formerly enslaved and free, to habitants – African and European merchants, traders, and residents, primarily in Saint-Louis – the most important and vibrant economic entity in urban Senegal. Of the habitants, the signares – mixed-race women ( métis ) – played a major role in shaping guardianship that subsequent chapters explore. The introduction ends with an outline of the chapters that encompass the social condition of children in tutelle in colonial Senegal from 1848 to 1910.

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)0.002
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: Other
Teacher disagreement score0.286
Threshold uncertainty score0.958

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.2860.101

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 head0.029
GPT teacher head0.216
Teacher spread0.187 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicAfrican history and culture studiesFrench-language works237,207