MétaCan
Menu
Back to cohort
Record W2118369482 · doi:10.7196/sajbl.7

Withholding and withdrawing treatment : practical applications of ethical principles in end-of-life care

2008· article· en· W2118369482 on OpenAlexaff
Liz Gwyther

Bibliographic record

VenueSouth African Journal of Bioethics and Law · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsCanadian Hospice Palliative Care Association
Fundersnot available
KeywordsBeneficenceBioethicsAutonomyDignityEconomic JusticeEngineering ethicsPsychologyEnd-of-life carePsychological interventionStatement (logic)NursingMedicinePalliative careLawPolitical science

Abstract

fetched live from OpenAlex

Many people fear the process of dying rather than the fact of dying. This fear is often associated with interventions that may be undertaken at the end of life as well as with the knowledge that suffering may be a part of dying and that both may be associated with loss of dignity of the individual. The paper discusses the statement that withholding or withdrawing treatment can be considered a sound clinical decision when reached in discussion with the patient (if competent), the family and the clinical care team. This decision is not taken lightly and it may not be easy to reach consensus on the decision. It is therefore important that the discussion and decision making are based on established bioethical principles. In the practical setting of care for patients at the end of life the four principles of ethics articulated by Beauchamp and Childress 1 are a useful guide for the clinical team. It is important to determine the goals of care and to enter into the discussion with these goals in mind. Treatment should then be focused on achieving realistic goals of care within an ethical framework. Beauchamp and Childress articulated four principles of bioethics: respect for autonomy, beneficence, non-maleficence and justice.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.214
GPT teacher head0.426
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueSouth African Journal of Bioethics and LawSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207