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Record W4381328093 · doi:10.3828/qs.2023.10

Mothering and Care Work in Indigenous Cinema from Québec

2023· article· en· W4381328093 on OpenAlexaboutno aff
Ioana Vartolomei Pribiag

Bibliographic record

VenueQuebec Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousContext (archaeology)Film directorGender studiesGenocideTributeSociologyMovie theaterPolitical scienceMedia studiesHistoryLawArt history

Abstract

fetched live from OpenAlex

The recent media focus on unmarked graves at former residential schools throughout Canada has brought fresh discussion of the particular role played by these institutions in the physical and cultural genocide of First Nations peoples. Yet, beyond the residential schools, the shattering of intergenerational ties has been pursued with purpose through manifold attacks on women, mothers, and children, as well as through the suppression of broader communities of care. This article provides a condensed overview of the institutionalized violence targeting First Nations women and children, supporting the notion that, in this context, mothering and care work become intrinsic modes of resistance to genocide. The article goes on to examine cinematic representations that contribute to decolonizing Indigenous motherhood. While important recent work by “relève autochtone” filmmakers pays tribute to strong Indigenous mothers, this article first looks at the roots of this decolonial turn in First Nations’ maternal representation, returning to the corpus of Alanis Obomsawin. It then analyzes two relève autochtone films, Mohawk filmmaker Sonia Bonspille Boileau’s Le Dep (2015) and Chloé Leriche’s Avant les rues (2016), arguing that, while these films may at first seem in some ways complicit with settler stereotypes, they ultimately present a broader, empowering understanding of mothering and care in First Nations communities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.324
Teacher spread0.297 · 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 teacher head, not a consensus.

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
Published2023
Admission routes1
Has abstractyes

Explore more

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