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Record W4308387708 · doi:10.1177/13634615221135423

No time to grieve: Inuit loss experiences and grief practices in Nunavik, Quebec

2022· article· en· W4308387708 on OpenAlexafffundabout
Shawn Renée Hordyk, Mary Ellen Macdonald, Paul Brassard, Looee Okalik, Louisa Papigatuk

Bibliographic record

VenueTranscultural Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsMcGill University Health CentreMcGill UniversityUniversité du Québec à Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsGriefGrassrootsDisenfranchised griefPsychologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

This article presents an overview of past and current grief rituals and practices and existing grassroots and institutional initiatives seeking to address the complex, prolonged, and traumatic grief experienced by many Inuit living in Quebec. While conducting a study seeking to identify the strengths, resources, and challenges for Nunavik's Inuit communities related to end-of-life care, results emerged concerning how family caregivers' grief related to the dying process was compounded by the sequelae of historic loss experiences (e.g., losses related to Canada's federal policies, including residential schools, forced relocations, and dog slaughters) and by present loss experiences (e.g., tragic and sudden deaths in local communities). To better support caregivers, an understanding of these grief experiences and a vision of bereavement care inclusive of community mobilization efforts to develop bereavement training and support is needed. We conclude with a discussion of a community capacity approach to bereavement care.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.022
GPT teacher head0.337
Teacher spread0.315 · 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 teacher head, not a consensus.

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

Citations4
Published2022
Admission routes3
Has abstractyes

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