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Record W7065984816

ââHere at the Brinkâ: Don McKayâs edge poetics and the articulation of wilderness in Canadian poetryâ

2018· other· en· W7065984816 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typeother
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPoeticsParallelsPoetryArticulation (sociology)SituatedBeholdWildernessNatural (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study is to interrogate how select English Canadian poets have broached the unknowability of an elusive subject in the natural world, paradoxically articulating the unspeakable or ineffable. This study focusses most explicitly on the edge poetics of contemporary Canadian poet Don McKay. Reading McKay’s oeuvre for poems situated at or within edges, thresholds, and peripheries, this research analyzes how McKay’s poetry problematizes the ever-categorizing mind, thereby challenging our perception of the non-human other in his work. Drawing a line of influence back through the tradition from which he comes, this study first surveys a long history of Canadian nature poems (1888-1966). Examining five poems that confront the “inappellable” (Scott, “Height of Land”), the first chapter shows how five English Canadian poets (Lampman, D.C. Scott, Pratt, A.J.M. Smith, Atwood) play with a poetics of unknowing to resist articulation of the non-human other they describe. The second chapter investigates parallels between Al Purdy and Don McKay. Purdy’s poems create room to behold mysterium tremendum—a concept that parallels McKavian wilderness. In the third and final chapter, this study focuses on McKay’s edge poetics, revealing how his poems gesture at a non-linguistic space. I conclude by showing the ethical potential of this poetics of “unknowing” the other.

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)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0160.020
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.213
Teacher spread0.204 · 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
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
Published2018
Admission routes1
Has abstractyes

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