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Record W4403709514 · doi:10.24135/dcj.v6i2.63

Searching for Justice: Indigenous Self-Determination over the Landfill Search as a Matter of Justice for MMIWG2S

2024· article· en· W4403709514 on OpenAlexaffabout
Leon Laidlaw

Bibliographic record

VenueDecolonization of Criminology and Justice · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsIndigenousEconomic JusticeEnvironmental justicePolitical scienceCriminologySociologyEnvironmental scienceLawEcologyBiology

Abstract

fetched live from OpenAlex

“Search the Landfill” is an Indigenous-led movement for justice for missing and murdered Indigenous women, girls, and Two-Spirit people (MMIWG2S) which originated through Indigenous resistance to police racism in Winnipeg, Canada. The movement calls upon all levels of government to support and execute the search of the Prairie Green Landfill, just north of the City of Winnipeg, to recover the bodies of at least two of four First Nations women who were murdered in early 2022 at the hands of a white male serial killer. Through an analysis of the news articles, press releases, and reports, this paper explores the way in which Indigenous leaders resisted and rewrote the discourses that surrounded the search. By at once condemning the Winnipeg Police Service’s refusal to search the landfill and rejecting police authority and control over the decision-making process, Indigenous women who became the leaders of this movement crafted the space to articulate for themselves how and why the search must be done as a matter of Indigenous rights. This paper explores how Indigenous leadership offers glimpses of what a decolonizing approach to justice may look like in cases of MMIWG2S and which, in turn, invites further opportunities to problematize, subvert, and move beyond the Western legal norms and traditions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.333
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2024
Admission routes2
Has abstractyes

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