Busting the Myth of the Non-Social Gamer: Comparing Friendship Quality Between Gamers and Non-Gamers
Bibliographic record
Abstract
Beyond the use of social media, people now often connect with people around the globe through online gaming. There are more than one billion people worldwide who play online games, and almost one-half of the population in the U.S are video gamers (Liu, Li, & Santhanam. 2013). There are still common stereotypes that gamers lack “real” friends and hide away from social activities as social isolates because the online world is not conducive to healthy social connections (Nie, 2001, Shen & Williams, 2010; Williams, 2006). However, there are also studies showing that online connections between gamers are healthy. Research with MMORPG players found that game play helped created strong online friendships, and social motives drove player participation (Griffiths et al., 2011). A German study showed that there was no significant difference between gamers and non-gamers in terms of how to socialize with other people online (Domahidi, Festl & Quandt, 2014). To gain a better understanding of gamers’ social characteristics, the present study examined friendships in online and offline domains in a gamer group and a non-gamer group. Ninety-two gamers and fifty-nine non-gamers completed the McGill Friendship Questionnaire (Mendelson & Aboud, 2014). for their closest online and offline friend, and a general measure of personal happiness using the Oxford Happiness Questionnaire (Hills and Argyle, 2002). Within group comparison found that for gamers the online friendship was of significantly higher quality than the offline friendship. For non-gamers, the opposite results were found. Of particular importance and interest in this study was the finding that the closest online friendship for the gamer group was not significantly different on any friendship dimension than the closest offline friendship for the non-gamer group, and both groups also showed no difference in general life happiness. In essence, the closest face to face friendship non-gamers enjoy looks the same as the closest online friendship reported by gamers. The results support the conclusion that gamers do have close and important friendships with other people, and that these occur online rather than face to face. The explanation could be that for gamers, their comfort in the online environment allows them to meet and grow close to others within this milieu, even though they may never meet their closest friend face to face. For further study, it will be valuable to see how this finding varies by personal qualities, such as gender, age or loneliness level.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".