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Record W4412019446 · doi:10.1080/03050068.2025.2524915

From comparison to complexity: the trans-continuous path of poetry education

2025· article· en· W4412019446 on OpenAlexaff
Victor Garfield

Bibliographic record

VenueComparative Education · 2025
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoetryPath (computing)Political scienceSociologyLiteratureComputer scienceArt

Abstract

fetched live from OpenAlex

This paper proposes a trans-continuous framework for rethinking poetry education, one that challenges and moves beyond traditional comparative models. Drawing on Chinese, Japanese, and English poetic traditions, it introduces trans-continuity as a theoretical lens for understanding how systems evolve through dynamic interaction, overlapping histories, and contextual adaptation. Rather than viewing global educational flows as linear or unidirectional, the paper highlights how cultural forms such as poetry emerge from interwoven continuities shaped by both affordance and adaptation. It critiques conventional dichotomies – such as East and West, global and local, original and borrowed – and emphasises context as the connective medium within complex systems. Through this lens, the paper re-examines Sadler's question on learning from ‘foreign’ systems, arguing that ‘foreignness’ emerges from shifting perspectives within a shared complex system. The study advocates a shift from comparison to complexity, viewing language, tradition, and culture as co-evolving strands in a dynamic trans-continuous web.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0060.043
Scholarly communication0.0120.024
Open science0.0010.015
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.103
GPT teacher head0.462
Teacher spread0.358 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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