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Record W3013955756 · doi:10.1353/his.2019.0068

L’indemnité coloniale de 1849 : Mise en place à répartition en Martinique et en Guadeloupe

2020· article· fr· W3013955756 on OpenAlexvenueno aff
Jessica Balguy

Bibliographic record

VenueHistoire sociale · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMartiniqueArtPolitical scienceSociologyWest indiesEthnology

Abstract

fetched live from OpenAlex

Lorsqu'en 1848 le gouvernement français met un terme à l'esclavage, il se donne aussi pour ordre d'indemniser les anciens propriétaires des colonies. Grâce à la loi du 30 avril 1849 et à son décret d'application du 24 novembre 1849, 126 millions de francs ont ainsi été attribués à des milliers d'individus, dont la diversité insoupçonnée tend à ébranler certains « mythes » construits autour de la figure du propriétaire comme étant nécessairement homme et « blanc ». Les listes exhaustives et informatisées des indemnitaires de la Martinique et de la Guadeloupe, qui recensent près de 6 000 noms, permettent en effet de produire des statistiques sur les femmes et les libres de couleur propriétaires d'esclaves en 1848. Abstract: When the French government abolished slavery in 1848, it also awarded financial compensation to former slave owners in the colonies. The law of April 30, 1849 and its implementation by the order of November 24, 1849 distributed 126 million francs among a diverse group of individuals. An analysis of the demographic make up of this group undermines the notion that slave owners were necessarily male and "White." Using a comprehensive and digitized list of individuals who received compensation in Martinique and Guadeloupe, which contains nearly 6,000 names, this article assesses the involvement of women and free people of colour who owned enslaved people in 1848.

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)0.003
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 score0.579
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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