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Record W2262179948 · doi:10.26443/ijwpc.v1i1.15

Caring for the Lived Experience: An Exercise in Teaching Whole Person Care

2014· article· en· W2262179948 on OpenAlexvenueno aff
Cory Ingram

Bibliographic record

VenueInternational Journal of Whole Person Care · 2014
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsDignityCompassionAttunementGriefLived experienceExistentialismNarrativeEmpathyPalliative carePsychologyNursingMindfulnessMedicinePsychotherapistMedical educationAlternative medicineSocial psychology

Abstract

fetched live from OpenAlex

Common medical professions’ education for whole person care of seriously ill people and their family is often lacking. The balance of educational attention to the biology of disease often far outweighs similar attention to the lived experience of the illness and personal caring. In an attempt to test and teach the lived experience a written essay survey instrument has been created and administered to new palliative care staff and family medicine residents.A summary of the participant’s responses to questions concerning ethical principles, dignity, health care desires, compassion, existential suffering, hope, grief, mindfulness, attunement, and end of life care will be shared in narrative fashion accompanied with teaching points used with participants. Third year family medicine residents’ reflections will be shared to reflect the impact of the teaching of whole person care.

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)0.026
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.041
Scholarly communication0.0130.012
Open science0.0020.018
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.123
GPT teacher head0.496
Teacher spread0.373 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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