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Record W4282964558 · doi:10.5014/ajot.2022.047357

What If Deliberately Dying Is an Occupation?

2022· article· en· W4282964558 on OpenAlexafffund
Manon Guay, Marie-Josée Drolet, Nicolas Kühne, Claudia Talbot-Coulombe, W. Ben Mortenson

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of British ColumbiaHealth and Social Services Centre University Institute of Geriatrics of SherbrookeUniversité du Québec à Trois-RivièresUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsPsychology

Abstract

fetched live from OpenAlex

In some legal and societal circumstances, people freely and capably plan, organize, and precipitate their own death. Drawing on published literature, we critically reflect on how deliberately ending one's own life fits with the current definitions of the concept of occupation. Using an occupational science and occupational therapy theoretical reflection, we argue that deliberately dying can for some people be considered a purposeful and meaningful occupation. Implications for such an occupational therapy practice are discussed: attending to the occupational needs of specific groups of people, reconsidering definitions and conceptual work, advocating for occupational justice in ending life activities, reflecting on ethical conundrums around self-harm activities within the scope of practice, and exploring deliberate death as a purposeful and meaningful occupation. Because deliberately dying is something that some people do, in this article we aim to open a dialogue within the field of occupational science and occupational therapy about this sensitive and potentially controversial issue.

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)0.015
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.058
Scholarly communication0.0120.014
Open science0.0010.005
Research integrity0.0080.008
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 head0.245
GPT teacher head0.524
Teacher spread0.279 · 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 designTheoretical or conceptual
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
Published2022
Admission routes2
Has abstractyes

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Same venueAmerican Journal of Occupational TherapySame topicOccupational Therapy Practice and ResearchFrench-language works237,207