MétaCan
Menu
Back to cohort
Record W4247171463 · doi:10.3138/cras.38.3.375

Death and the Maidens: Vancouver's Missing Women, the Montreal Massacre, and Commemoration's Blind Spots

2008· article· en· W4247171463 on OpenAlexvenueaboutno aff
Laurie S. McNeill

Bibliographic record

VenueCanadian Review of American Studies · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeGriefRhetoricResistance (ecology)CriminologyGender studiesStatus quoSubject (documents)SociologyHistoryMedia studiesPolitical scienceLawPsychologyLiteratureArt

Abstract

fetched live from OpenAlex

In this study, I focus on memorial responses to two crimes, the Montreal Massacre and Vancouver's so-called “Missing Women” serial killings, both large-scale, very public acts of violence targeted specifically at women. Comparing the memorializing of these mass murders, I analyse the complexities and the possibilities of contemporary memorial rhetoric and the issues of accessibility and legibility it raises; the gap between official and marginalized mourners (and victims) evident in these case studies stands as both a means of maintaining the status quo and an opportunity for resistance to these norms. Looking at particular commemorative acts, I explore how traumatic deaths—and the lives behind them—are remembered by the survivors, their communities, and the nation at large. Because memorials in their sundry forms bring together individual and public grief, personal and collective memory, and, in so doing, determine whose lives count to the community, they provide rich subject matter for analysing how death and life together contribute to auto/biographical identities and narratives.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0210.022
Scholarly communication0.0080.002
Open science0.0010.004
Research integrity0.0020.003
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 head0.063
GPT teacher head0.275
Teacher spread0.213 · 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 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

Citations4
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Review of American StudiesSame topicRhetoric and Communication StudiesFrench-language works237,207