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Record W2323864297 · doi:10.2190/om.63.2.e

Perinatal Loss and Parental Grief: The Challenge of Ambiguity and Disenfranchised Grief

2011· article· en· W2323864297 on OpenAlexafffund
Ariella Lang, Andrea R. Fleiszer, Fabie Duhamel, Wendy Sword, Kathleen Gilbert, Serena Corsini‐Munt

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2011
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsMcMaster UniversityUniversité de MontréalVictorian Order of Nurses
FundersCanadian Institutes of Health ResearchMcGill University Health Centre
KeywordsGriefDisenfranchised griefAmbiguityDistressPsychologyTraumatic griefDevelopmental psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Following perinatal loss, a type of ambiguous loss, bereaved couples struggle with and experience distress due to various forms of ambiguity. Moreover, the juxtaposition of their grief with society's minimization often disenfranchises them from traditional grieving processes. The purpose of this study was to explore sources of ambiguity and disenfranchised grief related to perinatal loss. Audio-taped interviews with 13 bereaved couples at 2, 6, and 13 months following the death of their fetus or infant were analyzed. Several categories of ambiguity and disenfranchised grief emerged, pertaining to: (a) the viability of the pregnancy; (b) the physical process of pregnancy loss; (c) making arrangements for the remains; and (d) sharing the news. This study uncovers the many sources of ambiguity and disenfranchised grief that bereaved couples face in interactions with family, friends, society, and healthcare professionals. These insights may inform healthcare professionals in their attempts to ease distress related to perinatal loss.

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)0.004
metaresearch head score (Gemma)0.017
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 score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0040.004
Open science0.0000.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.315
Teacher spread0.264 · 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

Citations245
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueOMEGA - Journal of Death and DyingSame topicGrief, Bereavement, and Mental HealthFrench-language works237,207