Virtual harassment: media characteristics' role in psychological health
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Using the stressor‐strain model and media richness theory, this study seeks to investigate the relationship between receiving a harassing message via computer‐mediated communication and psychological health. Design/methodology/approach A sample of 492 individuals completed an online questionnaire. Three media characteristics are examined as potential moderators: media richness, anonymity of the harasser, and location where the victim received the harassing message. Findings The results suggest that virtual harassment is associated with diminished psychological health (both directly and mediated by fear of future harassment), and each media characteristic plays a role in understanding the level of fear of future harassment. Anonymity and location moderate the mediator's (fear) role in the stressor‐strain model. Research limitations/implications This research addresses the need for explicit testing of the differentiating factors of various forms of workplace aggression as moderators. Specifically, media characteristics are relevant in the psychological experience of virtual harassment. Practical implications Virtual harassment appears to occur more frequently than face‐to‐face harassment, and often the two forms co‐occur. Implications for EAP counselors, computer usage and harassment policies are discussed. Originality/value This study is the first to examine how media richness, anonymity and location of harassing message impacts the individual outcomes of workplace non‐sexual virtual harassment. The results indicate that, while related to face‐to‐face harassment, virtual harassment appears to have more nuanced considerations for both practitioners and researchers.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it