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Record W2890090087 · doi:10.1386/public.29.57.236_1

THE NiS+TS PSYCHOGEOGRAPHER’S TABLE: Countering the Official Halifax Explosion Archive

2018· article· en· W2890090087 on OpenAlexaffabout
Mary Elizabeth Luka, Brian Lilley

Bibliographic record

VenuePublic · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsDalhousie UniversityUniversity of Toronto
Fundersnot available
KeywordsMateriality (auditing)NarrativeStorytellingInvisibilityVisual artsHistoryMedia studiesSculptureSubject matterSociologyArt historyAestheticsArtLiteratureComputer science

Abstract

fetched live from OpenAlex

Abstract The material culture of archives is reconsidered in the Psychogeographer's Table (PGT), a counter-archive created by the Narratives in Space + Time Society (NiS+TS) in response to the impending centenary of the accidental catastrophe of the 1917 Halifax Explosion (HE). The PGT counter-archive addresses the relationship between viewer and archive material in a number of novel ways. The subject matter of the archive considers the public geographies shaping our cultural landscape in the Explosion’s debris field, including the militarization of the waterfront and the invisibility of certain racialized and classed communities. The PGT is a portable sculpture and a curated repository of archival materials generated by NiS+TS, exhibited at the Dalhousie University Art Gallery in the fall of 2017. Further, the PGT’s unique materiality is reflected through multiple layers of mapping created through collaborative walking, augmented reality experiences and storytelling. These engagements situate the viewer within the archive, past and present, contrasting the everyday with the catastrophic event.

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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.975
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0120.013
Scholarly communication0.0140.007
Open science0.0010.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.001

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 head0.044
GPT teacher head0.332
Teacher spread0.287 · 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 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
Published2018
Admission routes2
Has abstractyes

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