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Race, Power, and Internal Orientalism in the U.S.: Reflections on Edward Said and the Responsibilities of Intellectuals

2005· article· en· W257261346 on OpenAlexvenueno aff
David Jansson

Bibliographic record

VenueArab world geographer · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsOrientalismInjusticePower (physics)SociologyLawPerspective (graphical)Scale (ratio)White (mutation)Political sciencePhilosophyTheology

Abstract

fetched live from OpenAlex

Edward Said advocated an activist role for intellectualsand argued for their responsibility to speaktruth to power and to ally with the “weak andunrepresented.” This article examines the ethics ofresponsibility on the part of the intellectual from ageographic perspective. It uses the example ofinternal orientalism in the United States to showthe usefulness of considerations of scale to themoral calculus of the politically engaged intellectual.It begins with a brief review of the issue ofpower within Orientalism, as described by Said,and the responsibility of the intellectual in thatcontext. It then examines these issues in thecontext of internal orientalism in the United States.“The South” is considered as an internal spatialother in the United States, but within this otheringthere are two others, African-Americans and white“Southerners.” The responsibility of the intellectualto each is discussed, and the appropriate stanceof the intellectual on the U.S. Civil War is examinedin this light. The explicit use of scale revealsthe possibility that one may judge the injustice atthe regional scale (slavery) as outweighing anyinjustice created by the power imbalance at thenational scale. In addition, the responsibility of theintellectual to the others of internal orientalisminvolves illuminating the process through whichthe spatial identities are constructed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
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 head0.015
GPT teacher head0.307
Teacher spread0.292 · 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.

Study designQualitative
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

Citations4
Published2005
Admission routes1
Has abstractyes

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