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Record W4376641016 · doi:10.1002/ijop.12916

Meaning and blame: Meaning threats increase victim blaming, but profession and art can diminish it

2023· review· en· W4376641016 on OpenAlexaff
Jason P. Martens, Shimaila Ayaz, S.Z. Ayaz, Gemma Dearn

Bibliographic record

VenueInternational Journal of Psychology · 2023
Typereview
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsCapilano University
Fundersnot available
KeywordsMeaning (existential)PsychologyBlameSocial psychologyAffect (linguistics)AestheticsPsychotherapistPhilosophyCommunication

Abstract

fetched live from OpenAlex

Previous work suggests that people have a need for meaning, and that when meaning is threatened, efforts are undertaken to restore a sense of meaning. We hypothesized that a meaning threat (i.e., reminders of death) would increase victim blaming of a domestic violence victim since doing so can restore a sense of meaning-that people get what they deserve-but for those with advanced knowledge of victimology, such as trained counsellors, this effect would be diminished since victim blaming runs counter to their meaning framework that bad things can happen to good people. In addition, because art can provide a sense of meaning, we hypothesized that either creating meaningful art or observing art and finding meaning within it would diminish blaming a domestic violence victim since having a sense of meaning should diminish the need to restore meaning via victim blaming. Over five studies with undergraduate and trained counsellors, we found support for the hypotheses, and a meta-analysis on the victim blaming effect suggested a small, though significant, effect size of d = .28. These findings enhance our understanding of various factors that affect victim blaming, and they point towards relatively easy to administer interventions to diminish it.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.466
Teacher spread0.371 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2023
Admission routes1
Has abstractyes

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