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Record W2800982751 · doi:10.7202/1058273ar

Haiku, Spiritual Exercises, and Bioethics

2019· article· en· W2800982751 on OpenAlexvenueno aff
James Dwyer

Bibliographic record

VenueCanadian Journal of Bioethics · 2019
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsHaikuBioethicsPoetryExistentialismReading (process)SpiritualityAestheticsPsychologySociologyEpistemologyPhilosophyMedicineLiteratureLawArtAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

Pierre Hadot has discussed the deep connections between ancient Western philosophy and spiritual exercises. The author appreciates these connections, but he explains why he explored a different path. He began to write haiku as a form of spiritual practice. He wanted to use these short verses to become more mindful, present, and responsive – in his life and in his work in bioethics. After comparing traditional haiku and modern haiku, the author gives some examples from classical sources. Then he considers how reading and writing haiku might help bioethics to focus less on deliberation and choice, and more on attention and perception. Haiku might help bioethics to attend to the contexts, life conditions, and lifeworlds that shape and situate people’s lives. These short poems might even illuminate some of the backgrounds and existential grounds of ethical life. At the end, the author presents some haiku that he wrote about modern life, young children, older adults, illness, medicine, and death.

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)0.004
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: Other
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.037
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.071
GPT teacher head0.362
Teacher spread0.292 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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