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Linda Hutcheon

2020· reference-entry· en· W4246298543 on OpenAlexaboutno aff
Geert Lernout

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsPostmodernismBachelorThe artsCriticismNarrativeVariety (cybernetics)SociologyArt historyArtVisual artsHistoryLiteratureComputer science

Abstract

fetched live from OpenAlex

Linda Hutcheon (b. 1947 as Linda Bortolotti) grew up in Toronto, where she did her honors bachelor of arts in modern languages and literatures, and where, after a master of arts in Romance studies at Cornell University, she also defended her doctorate in comparative literature. Hutcheon spent her early academic career as a professor of English at McMaster University before moving back to the University of Toronto in 1988, to the department of English and the Centre for Comparative Literature; she was made University Professor in 1996 and became emeritus in 2010. The impact of her work is felt in a number of distinct but related fields: in literary theory and history, in the study of Canadian literature and culture, in the definition(s) of postmodernism, and most recently, in collaboration with her husband Michael Hutcheon in the scholarly study of opera. Hutcheon’s main contribution to literary criticism may well be her work on the theory and practice of postmodernism, starting with her dissertation on what she then called narcissistic narrative. From a wide and varied theoretical background, she has defined and redefined the contours of postmodernism, doing so on the basis of the close study of postmodernist works in different disciplines: not just literature, but also architecture, music, and the visual arts. What distinguishes Hutcheon’s contribution to literary criticism and art theory is the width of her frame of reference, in terms of both the variety of the works that she has studied and of the critical approaches that she addresses in her own thinking. This width is also reflected in the numerous collaborative initiatives in which she has been involved during her long career: she is one of the few literary critics of her generation to have fully engaged in collaboration with many others, including her husband. With other scholars, she has written articles, published books, and edited special issues of journals and essay collections.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.750
Threshold uncertainty score0.836

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.2500.110

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 head0.035
GPT teacher head0.244
Teacher spread0.209 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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