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Record W3109540634 · doi:10.1016/j.wss.2020.100012

Locating death anxieties: End-of-life care and the built environment

2020· article· en· W3109540634 on OpenAlexaff
Michelle Knox

Bibliographic record

VenueWellbeing Space and Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDignityPalliative careEnd-of-life carePower (physics)Place of deathRight to dieQuality of life (healthcare)Good deathSociologyGerontologyNursingPublic relationsMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

As quality of life improves with better and more accessible healthcare, populations worldwide continue to age. Although fewer people die at home now than ever before, hospitals remain a significant site of death, while other locations—including hospices, long-term care residences, and cancer care centres—increasingly change social conceptions of ageing, dying, and palliative care. Within these rapidly changing scenarios, and in the wake of unprecedented industrial and technological progress, the palliative building is on the verge of disappearance. At this juncture, this paper asks whether—and how—the designed location figures into the end of life. Do places have the power to mediate our experiences of and attitudes towards dying? Since we have limited authority over how and what kills us, do we then root our control of, dignity in, and reconciliation with death based on where we die? Drawing links between architectural design and end-of-life studies, this paper will consider how we register—and may address—our anxieties around death and dying within built environments of 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 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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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