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Record W2946212927 · doi:10.1080/11745398.2019.1616572

The other side of suicide loss: the potential role of leisure and meaning-making for suicide survivors

2019· article· en· W2946212927 on OpenAlexaff
Julia Froese, Lisa McDermott, Yoshitaka Iwasaki

Bibliographic record

VenueAnnals of Leisure Research · 2019
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMeaning (existential)PsychologySocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Suicide rates are on the rise and subsequently more people, also known as suicide survivors, are left to grieve these types of losses. Yet, there has been limited examination and understanding of how individuals living through such experiences can potentially cope with and grow from this type of loss. Meaning-making through and engagement in leisure activities has been identified as a potential resource that may help individuals make sense of their lives and provide them with a liberating and healing opportunity. Therefore, the purpose of this conceptual paper is to identify the ways in which leisure may help individuals grieving suicide loss in their recovery, with a particular emphasis on how meaning-making and engagement through leisure may help to reinstate a more (a) joyful life, (b) connected life, (c) discovered life, (d) composed life, and (e) empowered life for suicide survivors.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0060.004
Open science0.0010.010
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.133
GPT teacher head0.466
Teacher spread0.333 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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