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Record W7032728349

“Our hearts are not at rest”: A critical look at the adequacy of Indigenous death investigations

2021· dissertation· en· W7032728349 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2021
Typedissertation
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousAccountabilityTheme (computing)Action (physics)Qualitative researchColonialism
DOInot available

Abstract

fetched live from OpenAlex

Across Canada, thousands of Indigenous testimonies have reported deficiencies in how police and medico-legal professionals investigate their deaths.The problem, however, is that these individuals are summarily and systematically denied the resources to challenge investigators and there are few cases that have done so successfully.This research establishes a comparative model to examine whether case investigation conduct aligns with standard investigative practice requirements.The qualitative sample includes three Indigenous case studies involving the suspicious deaths of young individuals in Prince Rupert, BC.The results present a central theme of inadequacy across all three cases, primarily in improper evidence collection, limited procedural follow-through, and withheld information.The outcomes of this study suggest a need for (1) future research and (2) professional action to create and uphold effective accountability measures for investigators and a critical look into how colonial powers limit investigative effectiveness for Indigenous deaths.

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)0.190
metaresearch head score (Gemma)0.294
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.999

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1900.294
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.003
Science and technology studies0.0520.100
Scholarly communication0.0230.016
Open science0.0050.015
Research integrity0.0080.015
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.281
Teacher spread0.245 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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