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Record W2404322161

Between Representations: Identity Crisis and the Bureaucratization of the University

2016· article· en· W2404322161 on OpenAlexaffabout
Gregory Cameron

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicRussian Literature and Bakhtin Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsArgument (complex analysis)SituatedContext (archaeology)Representation (politics)BureaucracyIdentity crisisSociologyIdentity (music)Meaning (existential)EpistemologyMedia studiesPolitical scienceSocial scienceLawPoliticsHistoryPhilosophyAesthetics
DOInot available

Abstract

fetched live from OpenAlex

“Between Representations” is an attempt to think the nature of the crisis of the university by re-engaging with the thought of Bill Readings and George Grant. The discussion is situated in the context of a more general crisis of representation manifest in recent attempts to celebrate Canada’s coming 150 years since Confederation. While the essay begins with an indication of the continuity of Readings’s with Grant’s argument, it focuses on Grant’s argument that the university today works to legitimate the techno-capitalist society of which it is a part and develops his suggestion that this is most significant in the context of the humanities and social sciences where it is least apparent. In developing Grant’s argument, the essay turns to questions of pedagogy and in particular the meaning and mode of engaging with “theory”. In considering the nature of theory, the paper suggests one possible mode of engaging with the crisis of representation that centres on work conducted in the classroom.

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)0.008
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.979
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0210.069
Scholarly communication0.0220.019
Open science0.0020.013
Research integrity0.0050.009
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 head0.182
GPT teacher head0.546
Teacher spread0.364 · 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.

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
Published2016
Admission routes2
Has abstractyes

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