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Record W7048919626

Missing and Murdered Indigenous Women, Girls, and Two-Spirit Trends in Canada

2022· article· en· W7048919626 on OpenAlexaboutno aff

Bibliographic record

VenueScholar Works (Boise State University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGovernment (linguistics)Law enforcementMissing dataPhase (matter)
DOInot available

Abstract

fetched live from OpenAlex

In North America, Indigenous women, girls, and Two-Spirit (IWG2) are at an increased risk of victimization. The matter long predates the present-day movement for a resolution. As a result, there is a severe data deficit regarding Missing and Murdered Indigenous Women, Girls, and Two-Spirit (MMIWG2) in Canada. On top of existing struggles within Indigenous communities, there is fear that they or a loved one will go missing at any moment and receive little to no aid in their recovery. Without adequate information, legislators cannot address the situation at hand. The MMIWG2 database provides this necessary information. The MMIWG2 research consisted of two phases. The first phase involved gathering over 1000 cases of MMIWG2 in Canada from media publications, government resources, and community databases. The second phase consisted of verifying the authenticity of each missing person's case and collecting corresponding information. This information included victim and offender demographics, time between an individual being reported missing and law enforcement responses, and if the case received follow-up or resolution. The verified information has allowed us to understand the effectiveness of Canada’s response to the issue, the overarching issue of MMIWG2, as well as allowed us to identify the dominant features of these cases.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0200.000

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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 designOther design
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
Published2022
Admission routes1
Has abstractyes

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