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Record W4405851864 · doi:10.1080/14725843.2024.2439422

Telling stories that cannot be told: remembering mothers and daughters in métis narratives from Rwanda

2024· article· en· W4405851864 on OpenAlexaboutno aff
Nicki Hitchcott, Alice Urusaro Uwagaga Karekezi, John D. McInally

Bibliographic record

VenueAfrican Identities · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
FundersArts and Humanities Research CouncilLeverhulme Trust
KeywordsNarrativeGender studiesHistoryPsychologySociologyLiteratureArt

Abstract

fetched live from OpenAlex

On the eve of independence in Ruanda-Urundi, hundreds of Métis children were taken from Catholic missions and flown to Belgium where they would be fostered, adopted, or sent to local boarding schools. These illegitimate children of white European fathers and Black African mothers were viewed by the colonial authorities as ‘children of sin’. Most of the Métis never saw their birth mothers again and remained illegitimate, unacknowledged by their white European fathers. In 2019, the Belgian government issued a formal apology for the abduction of these children but, for almost sixty years, the stories of the Métis and their mothers had been conveniently forgotten. This article discusses creative attempts to tell the missing stories of the Métis and their mothers by two mixed-‘race’ authors born in Rwanda: Georges Kamanayo, also a filmmaker, was removed from his mother in the late 1950s and taken to Belgium for adoption; Beata Umubyeyi Mairesse imagines the story of an ageing Métis woman with dementia in her novel, Consolée. Drawing on Saidiya Hartman’s concept of ‘critical fabulation’, we consider the role of creative works in repositioning Métis mothers and daughters at the centre of their own history and telling stories that cannot be told.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0180.023
Scholarly communication0.0080.008
Open science0.0020.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.291
Teacher spread0.253 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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