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Record W634564642 · doi:10.3138/9781442674769

Eye of the Heart: Knowing the Human Good in the Euthanasia Debate

2004· book· en· W634564642 on OpenAlexaboutno aff
William F. Sullivan

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2004
Typebook
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingValue (mathematics)EpistemologyTranscendence (philosophy)PsychologyEnvironmental ethicsPhilosophical methodologySociologySocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

What is the role of feelings in the euthanasia debate? This is the central question in William F. Sullivan's unique philosophical and ethical exploration of the issue, Eye of the Heart. Employing the principles and techniques of the great Canadian theologian and thinker Bernard Lonergan, Sullivan offers a concrete examination of the role of feelings in grasping moral values and the key role that feelings play in ethical decision-making. The heart has its reasons, he argues convincingly, and it is a type of reason that bioethicists, philosophers, and legal scholars all need to know. Sullivan draws on his experiences as a practicing physician to analyse the distinguishing elements of human knowing, illustrating them through common examples of decision-making in health care. He highlights the occurrence of various types of insight, particularly 'deliberative insights' that occur in the process of making value judgments. These deliberative insights are affective, and through them, a person apprehends moral values. Eye of the Heart proposes that feelings are relevant to knowing moral values and orient us towards moral self-transcendence. The implications of this stance in ethics are drawn out for the euthanasia debate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0010.013
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.378
Teacher spread0.298 · 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 teacher head, 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

Citations6
Published2004
Admission routes1
Has abstractyes

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