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Record W3208690421 · doi:10.32920/14657817.v1

Effects Of Virtual Reality (VR) On The Intention To Donate Money And Time: The Role Of Empathy, Guilt, Responsibility And Social Exclusion

2021· preprint· en· W3208690421 on OpenAlexaff
Maria Kandaurova

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsProsocial behaviorEmpathyDonationPsychologySocial psychologyAltruism (biology)MainstreamEmpathic concernSocial responsibilityContext (archaeology)Virtual realityPerspective-takingPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Virtual Reality (VR) technology has reached the mainstream market and is in the early stages of being used for charitable purposes. The aim of this research is to investigate and explain the effects of VR on empathy, guilt, responsibility, and donation of time and money in the social marketing context. Supported by the media richness theory (MRT) and the social presence theory (SPT), the results of three experimental studies suggest that VR, when compared to traditional two-dimensional video media (VM), increases empathy, increases responsibility, and encourages higher intention to donate and volunteer towards a social cause. Furthermore, it was shown that VR counteracts the negative effects of social exclusion on prosocial behaviour. In socially excluded participants, VR enhanced the level of guilt and social responsibility, leading to a higher intention to volunteer. Surprisingly, VR was not effective in promoting higher intention of money donation in socially excluded participants.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.708
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.003
Research integrity0.0000.001
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 head0.017
GPT teacher head0.302
Teacher spread0.286 · 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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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