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Record W2775952932 · doi:10.36510/learnland.v4i1.375

Poetry as Breath: Teaching Student Teachers to Breathe-Out Poetry

2010· article· en· W2775952932 on OpenAlexaffvenueabout
Lesley Pasquin

Bibliographic record

VenueLEARNing Landscapes · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPoetryHumanityPassionFeelingLiteratureThe artsArtClass (philosophy)Expression (computer science)AestheticsVisual artsPsychologyPhilosophyComputer scienceEpistemologyTheologySocial psychology

Abstract

fetched live from OpenAlex

Poetry is a form of creative expression that exists to share a truth, an insight, or a feeling that enriches our humanity."Teaching" poetry requires us to be readers and writers of poetry ourselves. It requires that we are saying, "Poetry matters." I work with second-year student teachers in my Language Arts Methods class at McGill University to develop a passion for the poetic; to learn what Muriel Rukeyser refers to as breathing-in experience and breathing-out poetry. Using my own writing process and immersing my students in the genre, they begin to construct the complex understanding of why poetry matters and why that understanding is crucial to teaching it.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0060.005
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.002

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 head0.017
GPT teacher head0.309
Teacher spread0.291 · 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 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

Citations4
Published2010
Admission routes3
Has abstractyes

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