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Record W2177618247 · doi:10.1177/0030222815574700

Holding On and Letting Go

2015· article· en· W2177618247 on OpenAlexaff
Shelley Raffin Bouchal, Lillian Rallison, Nancy J. Moules, Shane Sinclair

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2015
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsAlberta Children’s Hospital FoundationAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsGriefDisenfranchised griefPsychologyQualitative researchPsychotherapistDevelopmental psychologySociologySocial science

Abstract

fetched live from OpenAlex

Although grief and family caregiving have been extensively studied, there exists limited knowledge of anticipatory grief as it relates to families’ transition in illness to bereavement. Evidence suggests the need for a deeper understanding of the role that anticipatory grief plays to support families’ quality of life. The process of understanding is so embedded within our human nature that it is often left invisible in its everydayness. This qualitative pilot study was undertaken to explore the retrospective experiences of anticipatory grief of eight families who have lost a loved one from cancer. Findings revealed that family members lived in a complex tension of the duality of holding on and letting go throughout the illness and continued into bereavement. Retrospective reflection offered a deep awareness of the whole of the grieving process that included the understanding of grief in the midst of illness and its impact on postdeath grief.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.009
Scholarly communication0.0020.003
Open science0.0010.005
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 head0.084
GPT teacher head0.364
Teacher spread0.281 · 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

Citations34
Published2015
Admission routes1
Has abstractyes

Explore more

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