MétaCan
Menu
Back to cohort
Record W2936924585 · doi:10.1080/0966369x.2018.1553864

Mapping geographies of Canadian colonial occupation: pathway analysis of murdered indigenous women and girls

2019· article· en· W2936924585 on OpenAlexaffabout
Annita Lucchesi

Bibliographic record

VenueGender Place & Culture · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsIndigenousScholarshipNarrativeColonialismSociologyGender studiesOrder (exchange)HistoryPolitical scienceArtLiteratureEcologyLaw

Abstract

fetched live from OpenAlex

This paper builds on scholarship within life course studies, particularly notions of pathway analysis, to demonstrate how such analysis can be combined with cartography in order to be applied to studies of missing and murdered indigenous women, as a means to better understand the geographies of violence they live and die in. In this sense, this work utilizes the theoretical underpinnings of pathways analysis but transforms it into an indigenized tool for narration and analysis, by linking the pathways studied with relationships to land, colonialism, and intergenerational violence. By telling the narratives of the women studied in this paper in this way, this paper demonstrates that the binaries that are frequently applied to missing and murdered indigenous women create popular knowledge on this violence that is not necessarily reflective of reality, and that when we look beyond or between these binaries, different patterns and sites of violence emerge.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.011
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.256
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations35
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueGender Place & CultureSame topicIndigenous Health, Education, and RightsFrench-language works237,207