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Record W36527586 · doi:10.1007/s10554-022-02777-8

Traversing Locality/Navigating Borders

2010· article· en· W36527586 on OpenAlexaboutno aff
Kelly Thompson

Bibliographic record

VenueThe International Journal of Cardiovascular Imaging · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsLocalityTraverseComputer scienceGeographyCartography

Abstract

fetched live from OpenAlex

What is it to be located? What are the markers of communication that travel with us, or that we seek locally? Recent art practices that address notions of geography, migration, settlement and travel in an increasingly ‘globalized’ and mediatized world are presented in this paper. With Montreal, Canada as the site of location, this research explores ways in which experience intermingles in the poetics of visual translation of ‘real world’ imagery into textile-based responses. Travel and ‘the local’ suggests a map, a rhizome, consisting of multiple entry points “entirely oriented toward an experimentation in contact with the real”, as Deleuze and Guattari have observed. That the map is an ever-shifting terrain, conceived as a garden or work of art, woven as a political action or meditation, with potential to be reworked by an individual, group or social formation suggests the instability of identity, locality and of mapping. Focusing on interdisciplinary approaches to constructing cultural objects or experiences, this paper explores ways embodied knowledge affects both production and the sites in which stories are told. In particular, the impact of analogue and digitally assisted, cyborgian practices are compared in regards to bodily experience and subsequent haptic responses. These are textiles that conceptually navigate borders and traverse locality, mapping new meanings at the intersections of the corporeal, theoretical and material.

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)0.005
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.321
Teacher spread0.309 · 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
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

Citations0
Published2010
Admission routes1
Has abstractyes

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