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Record W2741637884

Les voix des femmes amérindiennes dans les littératures des Amériques

2016· article· fr· W2741637884 on OpenAlexaboutno aff
Anaïs Fouilleul

Bibliographic record

VenueINRIA a CCSD electronic archive server · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Jusqu’à quel point a pu évoluer la place de la femme dans les sociétés autochtones sous l’influence des sociétés patriarcales que sont les sociétés occidentales ? Cette interrogation engendre la question de l’image que peuvent avoir les différentes sociétés (autochtones et « nationales ») de l’Amérindienne et de ses conditions de vie actuelles. Aussi, ne serait-il pas intéressant d’obtenir le point de vue des principales concernées : les femmes amérindiennes ? Naomi Fontaine, Louise Erdrich et Eliane Potiguara sont trois auteures amérindiennes. La première auteure est issue de la communauté des Innus, au Québec, la seconde, est d’origine germano-chippewa et vit aux États-Unis et la dernière est issue des Potiguara, au Brésil. Ces trois Amérindiennes décrivent justement la condition de la femme autochtone à travers leurs écrits. Mais alors, comment ces auteures, faisant elles-mêmes partie de communautés autochtones, traitent-elles le sujet de la condition de la femme amérindienne ? Au sein de ce travail, nous tacherons d’étudier la représentation de la condition des femmes amérindiennes à travers l’étude de trois ouvrages d’auteures d’origine amérindienne : Kuessipan, à toi de Naomi Fontaine (Québec), Dans le silence du vent de Louise Erdrich (États-Unis) et Metade cara, metade máscara d’Eliane Potiguara (Brésil). Afin de répondre à cette problématique, certaines autres questions apparaissent, notamment la question de la pluralité des visions de l’Amérindienne.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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
Published2016
Admission routes1
Has abstractyes

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Same venueINRIA a CCSD electronic archive serverSame topicCanadian Identity and HistoryFrench-language works237,207