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Record W3155315688 · doi:10.2478/stap-2020-0013

Recent (Re)Visions of Canlit: Partial Stock-Taking

2020· article· en· W3155315688 on OpenAlexaboutno aff
Agnieszka Rzepa

Bibliographic record

VenueStudia Anglica Posnaniensia · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicModern American Literature Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousVisionSociologyInstitutionNewspaperColonialismMedia studiesAestheticsHistoryLiteratureLawSocial sciencePolitical scienceAnthropologyArt

Abstract

fetched live from OpenAlex

Abstract This article approaches recent discussions on the state of contemporary CanLit as a body of literary texts, an academic field, and an institution. The discussion is informed primarily by a number of recent or relatively recent publications, such asTrans.CanLit. Resituating the Study of Canadian Literature(Kamboureli & Miki 2007),Refuse. CanLit in Ruins(McGregor, Rak & Wunker 2018),Luminous Ink: Writers on Writing in Canada(McWatt, Maharaj & Brand 2018), and the discussions and/or controversies some of those generated – expressed through newspaper and magazine articles, scholarly essays, but also through tweets, etc. The texts have been written as a response to the current state and – in some cases – scandals of CanLit. Many constitute attempts at starting or contributing to a discussion aimed at not only taking stock of, but also reinterpreting and re-defining the field and the institution in view of the challenges of the globalising world. Perhaps more importantly, they address also the challenges resulting from the rift between CanLit as implicated in the (post)colonial nation-building project and rigid institutional structures, perpetuating the silencings, erasures, and hierarchies resulting from such entanglements, and actual literary texts produced by an increasingly diversified group of writers working with a widening range of topics and genres, and creating often intimate, autobiographically inspired art with a sense of responsibility to marginalised communities. The article concludes with the example of Indigenous writing and the position some young Indigenous writers take in the current discussions.

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)0.010
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0170.037
Scholarly communication0.0410.018
Open science0.0020.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0140.002

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 head0.066
GPT teacher head0.272
Teacher spread0.206 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2020
Admission routes1
Has abstractyes

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