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Record W4391706619 · doi:10.51644/9781554581108

By Word of Mouth

2007· book· en· W4391706619 on OpenAlexaboutno aff
Nicole Markotić, Dennis Cooley

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsWord (group theory)LinguisticsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Dennis Cooley, one of Canada’s most prominent poets, says writing becomes political when you play with certain kinds of voices. His poetry has been influenced and inspired by the prairies and other Canadian poets, but he insists on disturbing the formal poetic inheritance he esteems. His engagement with a variety of speaking voices asks that readers question authority and challenge institutional privilege. In By Word of Mouth , a collection from across his career, readers will discover how Cooley returns to the prairie vernacular and speaks to Canadian identity. Poetry, says Cooley, is about our time and our place. Nicole Markotić’s introductory essay discusses how Dennis Cooley plays with poetic reference, inspires with syntactical surprises, parodies contemporary writing, and indulges in wild, celebratory puns. This book roams around Dennis Cooley’s poetical world and invites the reader to play along.

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)0.006
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 score0.428
Threshold uncertainty score0.815

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0110.009
Open science0.0020.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.4280.486

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 head0.012
GPT teacher head0.215
Teacher spread0.202 · 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
Published2007
Admission routes1
Has abstractyes

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