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Record W2083264801 · doi:10.1080/07481180902961153

Early Parental Adjustment and Bereavement After Childhood Cancer Death

2009· article· en· W2083264801 on OpenAlexaff
Maru Barrera, Kathleen O’Connor, Norma Mammone D’Agostino, Lynlee Spencer, David Nicholas, Vesna Jovcevska, Susan Tallet, Gerald Schneiderman

Bibliographic record

VenueDeath Studies · 2009
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsWestern UniversitySickKids FoundationInstitute for Clinical Evaluative SciencesUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsPerceptionPsychologyDevelopmental psychologyChildhood cancerContext (archaeology)Adaptation (eye)GriefQualitative researchCancerPsychotherapistMedicineSociology

Abstract

fetched live from OpenAlex

This study comprehensively explored parental bereavement and adjustment at 6 months post-loss due to childhood cancer. Interviews were conducted with 18 mothers and 13 fathers. Interviews were transcribed verbatim and analyzed based on qualitative methodology. A model describing early parental bereavement and adaptation emerged with 3 domains: (1) Perception of the Child, describing bereavement and adjustment prior to and after the loss; (2) Perception of Others, including relationships with partners, surviving children, and their social network; and (3) Perception of the World, exploring parents' perceived meanings of the experience in the context of their worldview. Domains are illustrated by quotes. Profiles of parental bereavement emerged.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.041
GPT teacher head0.365
Teacher spread0.325 · 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 designObservational
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

Citations112
Published2009
Admission routes1
Has abstractyes

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