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Record W2329788721 · doi:10.2190/om.69.4.a

Online Survey as Empathic Bridging for the Disenfranchised Grief of Pet Loss

2014· article· en· W2329788721 on OpenAlexaboutno aff
Wendy Packman, Betty J. Carmack, Rachel Katz, France Carlos, Nigel P. Field, Craig Landers

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGriefDisenfranchised griefPsychologyBridging (networking)Complicated griefPsychotherapistSocial psychology

Abstract

fetched live from OpenAlex

The current cross-cultural study investigated grief reactions of bereaved individuals following the death of a pet. We used qualitative methodology to compare, analyze, and report responses of U.S. and French Canadian participants to the last open-ended question on our online pet loss survey. We explored the degree to which our data illustrated pet loss as disenfranchised grief and asked whether there are differences and commonalities in the expression of grief between the two samples. Four major themes emerged: lack of validation and support; intensity of loss; nature of the human pet relationship; and continuing bonds. Findings confirm that, for both the U.S. and French Canadian participants, pet loss is often disenfranchised grief and there are ways to facilitate expressions of grief. Many participants wrote that the survey was therapeutic. Our survey allowed participants to express their grief in an anonymous, safe way by serving as empathic bridging and a willingness to help others.

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)0.012
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.349
Teacher spread0.315 · 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

Citations63
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueOMEGA - Journal of Death and DyingSame topicHuman-Animal Interaction StudiesFrench-language works237,207