Peer contagion, lenient legal-ethical position, and music piracy intentions in emerging adults: Mindfulness as a protective factor
Bibliographic record
Abstract
Music piracy is a prevalent, costly, and illegal global phenomenon. The objective of this study was to test whether different facets of mindfulness (attention, present focus, awareness, and acceptance) moderated a mediation process in which digital piracy in friends promotes a lenient legal-ethical position that fosters music piracy intentions in emerging adults. We controlled for personality traits (Big Five), emotion regulation (reappraisal and suppression), time spent listening to music, various Internet-related behaviors (non-academic Internet use, downloading, social networking, smartphone use), and sociodemographics (gender, age, and level of education). Participants were 156 emerging adults (aged between 18 and 25 years) who studied at a Canadian university. Moderated mediation analyses (bootstrapping 50,000 random resamples) suggested that social influence from digital piracy in friends might be a risk factor that has: (i) a direct effect on music piracy intentions; (ii) an indirect effect on music piracy intentions via lenient legal-ethical position; and (iii) an effect on lenient legal-ethical position that can be buffered by attention, a facet of mindfulness that thereby acts as a protective factor. This study draws novel directions for research on the prevention of music piracy, notably the possibility that mindfulness is a protective factor against peer contagion of digital piracy in emerging adulthood.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".