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Imagining Spaces of Violence and Transgression in Vancouver and Northern Ireland

2019· book-chapter· en· W3002075539 on OpenAlexaboutno aff
Lizzie Seal, Maggie O’Neill

Bibliographic record

VenuePolicy Press eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownGender studiesContext (archaeology)Northern irelandMarine transgressionIndigenousGeographyScholarshipSociologyHistoryCriminologyPolitical scienceArchaeologyEthnologyLaw

Abstract

fetched live from OpenAlex

This chapter focuses specifically on the issue of space, place, violence and transgression drawing on case studies in Canada and Northern Ireland. ‘Imagining spaces of violence and transgression in Vancouver and Northern Ireland’ focuses first of all on the lives of indigenous women and sex workers in Vancouver’s Downtown Eastside (DTES). For 26 years, on 14 February, Valentine’s Day, women of the DTES have led a memorial march through the city, stopping at the places and spaces where women were murdered or went missing. The chapter draws on material from walking methods, participatory photographs and interviews with women who attended the march in 2016 to examine spaces of past, present and future in their lives. Continuing the theme of the construction and impact of space and borders explored in the previous chapter, this chapter also examines the history of the ‘peace walls’, ‘peace lines’ or ‘border lines’ in Belfast in the context of spaces of war, violence and conflict in Northern Ireland. Specifically,the ‘architecture of conflict’ is explored through criminological scholarship on the conflict in Northern Ireland. As with the Vancouver case study, arts-based walking methods are utilised that explore these border spaces through sensory, kinaesthetic, multi-modal research with citizens of Belfast.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.288
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2019
Admission routes1
Has abstractyes

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