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Record W4360981507 · doi:10.1080/14791420.2023.2169818

Subject to/flesh, object/to verb (:) the business of naming

2023· article· en· W4360981507 on OpenAlexaff
Louis M. Maraj

Bibliographic record

VenueCommunication and Critical/Cultural Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSubject (documents)Resistance (ecology)NarrativeWhite (mutation)PoliticsGrammarVerbNormativePower (physics)Object (grammar)SociologyLinguisticsDramatizationHistoryAestheticsLiteratureArtPolitical scienceComputer sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

How do quotidian speech-acts, lived experiences, and normative grammars/logics capture affects of antiBlack racism that co-constitute campus memory and landscapes beyond infrastructure and spectacular commemoration of exceptional past events/historical figures? How does Black resistance to white supremacist university structures (un)fold with/in them? This experimental essay considers power dynamics inherent in complaint about antiBlackness at an historically white U.S. campus amid 2020’s racialized pandemic violence. Through narrative-driven inter(con)textual reading, it toys with the politics of subject(ivity), t(h)inking through how names function rhetorically to reify what Hortense Spillers conjures as “American grammar,” while wrestling (in-and-of itself) with onto-linguistic violence in re/membering trauma.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.138
GPT teacher head0.392
Teacher spread0.254 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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