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Record W2460956719 · doi:10.1177/082585971002600304

La Belle Mort En Milieu Rural: A report of An Ethnographic study of the Good Death for Quebec Rural Francophones

2010· article· en· W2460956719 on OpenAlexaffabout
Anne‐Marie Veillette, Lise Fillion, Donna M. Wilson, Roger E. Thomas, Serge Dumont

Bibliographic record

VenueJournal of Palliative Care · 2010
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversité LavalHôtel-Dieu de QuébecMichel-Sarrazin
Fundersnot available
KeywordsEthnographyEthnic groupRural areaGood deathSociologyPsychologyGerontologyGender studiesMedicineNursingPalliative careAnthropology

Abstract

fetched live from OpenAlex

An ethnographic study was undertaken in two rural areas of Quebec to conceptualize the good death. The findings reveal that a good quality of life for the dying person and his or her family and friends is essential for a good death. The resulting conceptual model emphasized four dimensions: physical, spiritual, social, and emotiona/psychological. These dimensions were determined to be similar to those discovered through a previous urban study, indicating that there may be considerable overlap between good deaths in rural and urban areas. Some findings of this Quebec French-language rural study were similar to those of an Alberta English-language rural study, indicating that rural people may have some common needs and interests with regard to the good death. As such, there could be some common elements of the good death that transcend culture or ethnicity. Chief among these is the desire of rural people to die at home or in their home communities.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.090
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.420
Teacher spread0.365 · 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

Citations23
Published2010
Admission routes2
Has abstractyes

Explore more

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