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Record W4386137124 · doi:10.3406/ranam.2019.1576

Sites of Dissensus : Sensing Borders and Affective States

2019· article· en· W4386137124 on OpenAlexaboutno aff
Lee Rodney

Bibliographic record

VenueRecherches anglaises et nord-américaines · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American and Latino Studies
Canadian institutionsnot available
Fundersnot available
KeywordsReactionaryIndigenousHomelandContext (archaeology)PoliticsPolitical scienceSociologyRepresentation (politics)AestheticsPolitical economyHistoryLawArtArchaeology

Abstract

fetched live from OpenAlex

This essay considers the shifting representation of borders and territory in a North American context and how these sites continue to exert force on the political imagination through a language of crisis and emergency. While the creation of the Department of Homeland Security (2002) and the establishment of the U.S.-Mexico border wall (2006-8) are among the most obvious manifestations of a transformation in border policy, calls for greater protection along sparsely populated regions of the Canada-U.S. border have surfaced repeatedly in the media from 2017 onwards. In both the U.S. and Canada, the gaze toward “the border” has remained steady for some time. I argue that the relationship between sight and site was pressed into service in the creation and maintenance of national borders and that the mediated image of the border has been critical to shifting attitudes toward the role of borders and migration from the late 19th century onwards. But borders are also paradoxical sites that become knowable, however, as affective states. Drawing on the disparate work of Walter Mignolo and Jacques Rancière this paper explores the role of the senses in both historical and contemporary bordering processes through looking at a range of collaborative art and activist practices that align with relational and decolonial aesthetics. As the decolonial project becomes increasingly imperative for both indigenous and non-indigenous people in North America after the recommendations of the 2015 Truth and Reconciliation Report, I ask how the reactionary and populist forms of border fortification can be countered and unsettled by hemispheric perspectives and migratory routes.

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)0.005
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.017
Scholarly communication0.0090.008
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.384
Teacher spread0.312 · 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
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
Published2019
Admission routes1
Has abstractyes

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