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Record W2773822620 · doi:10.1177/0825859717717154

A Battle of Words

2017· article· en· W2773822620 on OpenAlexaff
Daniel Burnier

Bibliographic record

VenueJournal of Palliative Care · 2017
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBattleHistoryPsychologyMedicineAncient history

Abstract

fetched live from OpenAlex

This article analyzes the writings of Elisabeth Kübler-Ross through the discursive lens of the phrase "dying with dignity." For her, the phrase meant allowing someone to die comfortably his/her own death. This phrase has to be understood in relationship with the final "stage of acceptance" of her model. Describing this key part of her well-known scientific output, she often used, in the early 1970s, the phrase "dying in peace and dignity." An evaluation of the evidence suggests that because the concept of dignity was co-opted by the pro-euthanasia movement during this decade, the language of dignity was little by little abandoned by her. In later years, only "peace" survived from her favorite expression. Although this concept of peace remains present to the end in all Kübler-Ross writings, the pro-euthanasia movement has also started to speak the language of peace.

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)0.007
metaresearch head score (Gemma)0.026
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: Commentary · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0140.027
Scholarly communication0.0170.022
Open science0.0020.012
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0270.017

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 head0.107
GPT teacher head0.399
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
GenreCommentary

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

Citations8
Published2017
Admission routes1
Has abstractyes

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