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Record W4406732429 · doi:10.1080/07481187.2025.2454505

“The living need care”: Experiences of bereaved workers in precarious employment

2025· article· en· W4406732429 on OpenAlexaffabout
Karima Joy, Susan Cadell, Elizabeth Peter, Pia Kontos

Bibliographic record

VenueDeath Studies · 2025
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsNursingPsychologySociologyMedicine

Abstract

fetched live from OpenAlex

Bereavement scholarship predominantly examines psychological aspects of grief, which neglects the role of social, economic, and political factors that shape the space to accommodate these experiences. Responding to calls for enhancing bereavement care, this research explores bereavement accommodation for workers in precarious employment in Ontario, Canada. Drawing on critical qualitative research and feminist ethics, this study employed in-depth interviews to generate knowledge on the everyday experiences of bereaved workers in precarious employment. Participants expressed they were uninformed and unprepared for grief and practical bereavement labor, and that navigating the current context created tension, stress, exhaustion, isolation, and stigma. We argue the systemic neglect of bereavement is driven by socio-political forces that devalue relationality, stigmatize emotions, and render bereavement an individual responsibility. This research informs broad recommendations, including enhancing grief literacy, establishing safeguards for precarious workers, and creating more responsive care pathways and strategies for addressing individual and collective 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)0.003
metaresearch head score (Gemma)0.008
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 score0.162
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0260.020
Scholarly communication0.0050.003
Open science0.0020.012
Research integrity0.0020.006
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 head0.047
GPT teacher head0.392
Teacher spread0.346 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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