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Record W2604858360 · doi:10.3138/topia.36.79

In the Name of the National Multicultural Family: The Documentation of Honour Killings and the Pedagogy of Pain

2016· article· en· W2604858360 on OpenAlexvenueaboutno aff
Eve Haque

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsnot available
Fundersnot available
KeywordsHonourMulticulturalismSociologyFraming (construction)NarrativeGender studiesCycle of violenceDomestic violenceMedia studiesCriminologyLawPolitical scienceHistoryPedagogyArtLiteraturePoison control

Abstract

fetched live from OpenAlex

This article focuses on Shelley Saywell’s documentary film about honour killings, In the Name of the Family, which won the Best Canadian Feature Award at the 2010 HotDocs Documentary Film Festival. Saywell stated that her hope in making this documentary was that it would help educate in order to break the cycle of abuse. This goal will be explored to see if in fact this documentary can allow the audience to hear these young women who are the victims of honour killings and whether this translates into the pedagogic potential for which Saywell hopes. Saywell’s documentary is framed within a binaristic “clash of cultures” narrative, where the fate of these young Muslim women are the limit case of a crisis of multicultural tolerance. This framing obscures the material realities which underpin gendered violence and racial exclusion in Canada even as it secures the national fantasy of a tolerant multicultural society. Ultimately, this article argues that the epistemological constraining of the patriarchal violence in this film as a specific form of culturalized and essentialized patriarchal traumatic violence serves only to entrench a larger project of white settler multicultural nationalism and limits the possibilities of knowing to the primacy of the viewing subject.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.175
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.040
GPT teacher head0.397
Teacher spread0.357 · 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 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

Citations2
Published2016
Admission routes2
Has abstractyes

Explore more

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