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Record W3096746063 · doi:10.1089/pmr.2020.0012

Jesus Practiced Advance Care Planning: Biblical Basis and Possible Applications

2020· article· en· W3096746063 on OpenAlexaff
Grace Johnston

Bibliographic record

VenuePalliative Medicine Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsDalhousie University
Fundersnot available
KeywordsConceptualizationAdvance care planningExperiential learningPsychologyHealth carePoint (geometry)AestheticsSociologyNursingMedicinePhilosophyPolitical sciencePedagogyLawPalliative care

Abstract

fetched live from OpenAlex

Background: Persons from a Christian tradition may have concerns that impede advance care planning for end of life. Sharing how Jesus practiced advance care planning may provide a pivot point to help ameliorate this problem. Objective: To present a novel approach to advance care planning from a Christian tradition. Evolution of the Novel Approach: Experiential learning that resulted in the novel approach is described using Kolb's learning cycle: proceeding from concrete experience to reflective observation followed by abstract conceptualization and then active experimentation. Results: The novel approach builds on events toward the end of Jesus' life to demonstrate how he practiced advance care planning: telling those close to him that he was going to die even though they did not want to hear this, participating in a celebration of his life on Palm Sunday, sharing a Last Supper with those close to him, showing them how he wanted to be remembered, asking his friends to pray with him in the garden of Gethsemane, and saying to his mother that John would care for her. Questions related to these events are posed for use by health and spiritual care professionals to innovatively engage persons in advance care planning. Discussion: This approach might be adapted for persons of other religious traditions by exploring their sacred teachings. It is proffered for others to explore, adapt, and evaluate for its utility in initiating and facilitating advance care planning.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.158
GPT teacher head0.464
Teacher spread0.306 · 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 designObservational
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

Citations3
Published2020
Admission routes1
Has abstractyes

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