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Record W2060544889 · doi:10.3138/utq.83.1.12

In Memory of Edward Said – The Bulletproof Intellectual

2014· article· en· W2060544889 on OpenAlexvenueno aff
Ella Shohat

Bibliographic record

VenueUniversity of Toronto Quarterly · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPoliticsCourageOrientalismHybridityPresentation (obstetrics)Cultural studiesPassionSociologyFriendshipAestheticsLiteratureHistoryPhilosophyLawSocial scienceAnthropologyArtPolitical science

Abstract

fetched live from OpenAlex

This plenary presentation eulogizes Edward Said and speaks to his courage, passion, and scholarship, while simultaneously acknowledging his discomfort with the problematic category of “great men.” Shohat traces Said’s early scholarship, the vitriolic backlash against his words, and the way his work consolidated what would, a decade later, become the fields of postcolonial studies and cultural studies. Shohat’s presentation then delves into the circulation and reception of his critique of Orientalism as an example of “traveling theory.” In Middle East studies, Said has been criticized as a deficient political scientist or historian or anthropologist, with critics ignoring the central concern of his work: the problem of representation and the necessity of a political critique that is also a cultural critique. In postcolonial studies in Israel, a certain post-Zionist discourse privileged Homi Bhabha’s theories of hybridity, which were translated into Hebrew, over Said’s not-yet-translated and allegedly binaristic notions of coloniality. In the final moments of the presentation, Shohat reflects on her friendship with Edward Said, remembering his courage in the face of consistent attacks and his willingness to inhabit the ever-uncomfortable space of the worldly yet “out-of-place” intellectual.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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