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Record W4321443798 · doi:10.1080/08893675.2022.2161753

Understanding death within eternal poetic time

2023· article· en· W4321443798 on OpenAlexaff
Donard MacKenzie

Bibliographic record

VenueJournal of Poetry Therapy · 2023
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity Canada West
Fundersnot available
KeywordsPoetryLiteratureEphemeral keyPhilosophyAestheticsPsychoanalysisArtPsychologyComputer science

Abstract

fetched live from OpenAlex

This article is an a/r/tographic (artist/researcher/teacher) study through autobiographical close readings of several poems as a means to understand death within what the author calls eternal poetic time. Moving beyond the author’s childhood’s static image of death, the paper suggests that the ephemeral nature of life is not something to fear, but makes living more beautiful and eternal through the making and sharing of poetry and art. This paper is the first part of a three-paper study, which includes original poetry by the author.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.028
Scholarly communication0.0050.009
Open science0.0010.007
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.176
GPT teacher head0.390
Teacher spread0.214 · 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
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
Published2023
Admission routes1
Has abstractyes

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