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Record W4224940490 · doi:10.1177/00302228221093464

When a Child Dies: Racialized Father’s Experiences of Objectification During Hospital Care

2022· article· en· W4224940490 on OpenAlexaffabout
Linda Kongnetiman-Pansa, Rebecca Haines‐Saah

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2022
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsObjectificationGrounded theoryConstructivist grounded theoryImmigrationGriefQualitative researchGender studiesSociologyPsychologySocial psychologyDevelopmental psychologyPsychotherapistAnthropology

Abstract

fetched live from OpenAlex

Understanding the meaning of loss for racialized immigrant fathers and addressing their experiences in a culturally competent manner is important in an increasingly ethnoculturally diverse country like Canada. Culture, customs and rituals influence fathers' grief and culture impacts how individuals discuss death and dying as well as how they perceive the death of a child. This article is part of a qualitative research project, which examined the experiences of racialized immigrant fathers who experienced the death of a child. Guided by Charmaz's constructivist grounded theory, the methodological aim was to develop a theoretical framework grounded in fathers' experiences of child death within the hospital setting. Findings suggest that for racialized immigrant fathers their migration experience compounds their losses in unexpected ways and that experiences of objectification or 'othering' in hospital and by health care staff were significant.

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)0.005
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 score0.011
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0110.007
Scholarly communication0.0040.003
Open science0.0010.007
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 head0.021
GPT teacher head0.312
Teacher spread0.291 · 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 routes2
Has abstractyes

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