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Record W4411597659 · doi:10.1177/00302228251356055

Undergraduate Students’ Beliefs About Different Unusual End-of-Life Phenomena

2025· article· en· W4411597659 on OpenAlexaff
Stephen Claxton-Oldfield, Sophie Agnew, Ella Allen-Tanner, Erica Astephen, H K Batson, Janelle Belliveau, Makayla Boudreau, Emily Estabrooks, Marie P. Fogarty, Hailey Frampton, Talia Friesen, Chelsea Krahenbil, Theo Pink, Jaimee Sisk, Brooke Williams

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2025
Typearticle
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsMount Allison University
Fundersnot available
KeywordsAfterlifePsychologyPhenomenonSocial psychologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Ninety-seven undergraduate students responded to a survey regarding their beliefs about unusual end-of-life phenomena (EOLP). Previous studies have examined beliefs about EOLP collectively (i.e., as a single entity). The purpose of this study was to examine participants' beliefs about different EOLP separately. To that end, participants responded "yes", "no", or "unsure" to 36 statements about 18 different EOLP (two statements for each phenomenon). The results revealed that participants believed in some EOLP (e.g., 62% believed that pets behave strangely when their owner is about to die), disbelieved in some EOLP (e.g., 78% disbelieved that clocks and watches can stop when someone dies), and were uncertain about still others (e.g., 44% were unsure whether a dying person's deceased loved ones will be there to collect them when they die and take them on a journey to the afterlife). Limitations are discussed and suggestions for future research are offered.

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)0.011
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.349
Teacher spread0.320 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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