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Geography, Spatiality, and Racialization: The Contribution of Edward Said

2004· article· en· W2590354846 on OpenAlex
Audrey Kobayashi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueArab world geographer · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsQueen's University
Fundersnot available
KeywordsRacializationSociologyNegationRace (biology)SituatedPoliticsGender studiesColonialismSpace (punctuation)EpistemologyAnthropologyLawPolitical scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

For anti-racist geographers, Said's greatest contribution has been to provide some of the intellectual tools to advance the political project of overcoming the effects of a millennium of racialization. His recognition that the geographical imagination is fundamentally based upon a colonial history of the construction of the racialized Other has coincided with the development of an interest in racialization by critical geographers. Both geographers and cultural theorists have for the most part, however, relied upon a notion of space as either a container or a setting for race, rather than viewing spatiality as a form of human relationship, based on a double action of establishing distance and proximity. The practice of racialization involves the fundamental act of creating difference by setting the Other at a distance, while setting up a relationship of domination. Jean Paul Sartre's concepts of distance and negation allow for a complex, historically situated understanding of spatiality. Said contribut...

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.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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