Effects Of Virtual Reality (VR) On The Intention To Donate Money And Time: The Role Of Empathy, Guilt, Responsibility And Social Exclusion
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".