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Record W4361795916 · doi:10.4000/histoiremesure.16761

Documenting Interpersonal Conflict in Senegal during the First Quarter the Twentieth Century

2022· article· en· W4361795916 on OpenAlexaboutno aff
Karine Marazyan

Bibliographic record

VenueHistoire & Mesure · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Interpersonal communicationContext (archaeology)ColonialismPoliticsAdministration (probate law)Political scienceInterpersonal relationshipLawSociologyHistorySocial scienceArchaeology

Abstract

fetched live from OpenAlex

In the early twentieth century, in countries of former French West Africa, new adjudicatory bodies, the so-called “native courts,” were created and managed by the French colonial administration to handle disputes between native people. The monitoring of court activity generated high-frequency litigation data that provide a unique opportunity to document interpersonal conflict in a context of colonial rule undergoing rapid transformation. This paper has three objectives: (i) to describe the institutional framework that gave rise to the case registers, “Les États Récapitulatifs,” upon which this research is based; (ii) to detail our method for compiling time series of cases adjudicated by the native courts of Senegal; (iii) to describe certain time trends in the dynamics of cases adjudicated by these courts. We conclude by discussing how this database could be used to better understand the economic and political roots of interpersonal conflict.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.406

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.011
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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