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Record W4401205641 · doi:10.1080/10646175.2024.2326205

Indigenous Embodied Activism and Memory Politics for Missing and Murdered Indigenous Women

2024· article· en· W4401205641 on OpenAlexaboutno aff
Lara Lengel, Sadaf R. Ali, Shanna Gilkeson

Bibliographic record

VenueHoward Journal of Communications · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPoliticsGender studiesNarrativeClimate justiceSilenceMemory workPolitics of memorySociologyEconomic JusticeHonorRhetoricMedia studiesCriminologyPolitical scienceLawAesthetics

Abstract

fetched live from OpenAlex

This study aims to understand material and symbolic communication approaches surrounding Missing and Murdered Indigenous Women (MMIW), and the Indigenous and feminist memory work to honor MMIW. Indigenous women and girls in Canada have gone missing and have been murdered at six times the rate of their non-Indigenous counterparts. First Nations and Indigenous communities in Canada have engaged in protests and memory activism to raise awareness of violence against Indigenous women and seek increased support from the criminal justice system. Following an Indigenist and decolonizing memory work methodological approach developed by Gail Baikie (Inuit) and the rhetoric of survivance of Gerald Vizenor (Anishaabe), we analyze the Search the Landfill current protests at the Prairie Green landfill north of Winnipeg, Manitoba, Canada. Winnipeg police reported they believe four MMIW women’s remains are in the landfill. The study is vitally important as these protests and Indigenous advocacy efforts have never been analyzed and efforts continue to unfold. Analysis centers on public discourse on MMIW, counter/memory resistant efforts, embodied activisms of the protestors, efforts to silence and—literally—bury MMIW, and an understanding of how memory activism can amplify hushed narratives and energize counterattacks against erasures of memory.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
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 head0.039
GPT teacher head0.354
Teacher spread0.315 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

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