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Record W7028827328

Grief on the margins: The death of a family member to substance use

2025· article· en· W7028827328 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2025
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsDisenfranchised griefGriefShameFamily memberSubstance useSpiritualityTraumatic griefQualitative researchNarrative
DOInot available

Abstract

fetched live from OpenAlex

Despite Canada's high death rates from substance use, there is limited research on the sociopsychological impact on families, who often face stigma and disenfranchised grief. This study explores how family members make meaning of a substance-related death. Through qualitative inquiry, eleven family members were interviewed on their experience of grief from substance death. The imprint of losing a family member to mental illness and substance use is fraught with intergenerational grief, ambiguity, prolonged mental-emotional distress, and relationship challenges. Substance death was also associated with stigma, social withdrawal, and shame for many participants. However, grievers reconstructed the socially prescribed negative perceptions and treatment of families impacted by substance death through education, supportive community, art, and resistance. Spirituality and relationships with non-human kin also emerged as healing in grief. Through these common avenues, participants restory their narratives and embody the wise helpers they would have benefited from in vulnerable moments of grief. This study supports the need for substance death grief literacy and highlights the implications for social work practice.

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)0.009
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 score0.063
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0160.011
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.297
Teacher spread0.242 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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