MétaCan
Menu
Back to cohort
Record W4306404162 · doi:10.3917/re1.108.0106

Vivre le décès d’un proche en temps de pandémie

2022· article· fr· W4306404162 on OpenAlexaff
Chantal Verdon, Josée Grenier, Jacques Cherblanc, Chantale Simard, Christiane Bergeron‐Leclerc, Danielle Maltais, Emmanuelle Zech, Susan Cadell

Bibliographic record

VenueAnnales des Mines - Responsabilité et environnement · 2022
Typearticle
Languagefr
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à ChicoutimiConcordia UniversityMinistère de l’Emploi et de la Solidarité Sociale (Québec)Université du Québec en Outaouais
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

La pandémie suscite de nombreux questionnements liés au phénomène du deuil, où les circonstances entourant le décès d’un proche sont une source de connaissances extrêmement importantes et inédites permettant de mieux saisir l’importance des événements entourant un tel malheur. Une étude québécoise s’est intéressée à l’expérience de personnes ayant perdu un proche pendant la pandémie. Trois thèmes émergent de cette étude qui s’appuie sur des données qualitatives : le temps laissé ; le sens donné à cette épreuve ; et l’attitude du personnel soignant. L’étude livre des témoignages sur ce qui peut influencer les trajectoires du mourir et du deuil. De ces circonstances chaotiques et imprévisibles, les personnes endeuillées peuvent quand même y donner un sens quand elles peuvent poser des actes concrets : faire leurs adieux ; voir une dernière fois le défunt ; procéder à des rituels significatifs et recevoir une attention empreinte d’humanisme.

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)0.007
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 score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.008
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.037
GPT teacher head0.333
Teacher spread0.296 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAnnales des Mines - Responsabilité et environnementSame topicGrief, Bereavement, and Mental HealthFrench-language works237,207