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Record W630909963 · doi:10.1017/cbo9780511852077

Children's Understanding of Death

2011· book· en· W630909963 on OpenAlexaff
Paul L. Harris, Victoria Talwar, Michael Schleifer

Bibliographic record

VenueCambridge University Press eBooks · 2011
Typebook
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyDeath educationEpistemologySocial scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

In order to understand how adults deal with children's questions about death, we must examine how children understand death, as well as the broader society's conceptions of death, the tensions between biological and supernatural views of death and theories on how children should be taught about death. This collection of essays comprehensively examines children's ideas about death, both biological and religious. Written by specialists from developmental psychology, pediatrics, philosophy, anthropology and legal studies, it offers a truly interdisciplinary approach to the topic. The volume examines different conceptions of death and their impact on children's cognitive and emotional development and will be useful for courses in developmental psychology, clinical psychology and certain education courses, as well as philosophy classes - especially in ethics and epistemology. This collection will be of particular interest to researchers and practitioners in psychology, medical workers and educators - both parents and teachers.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.010
Scholarly communication0.0040.004
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.070
GPT teacher head0.268
Teacher spread0.198 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations28
Published2011
Admission routes1
Has abstractyes

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