We have always been social: Comparing social expressiveness between single-player and multiplayer gamers
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
Organizing games by categories based on playstyle (e.g. single-player vs. multiplayer) makes sense from a marketing perspective, but when it comes to organizing players into such categories, things get tricky. To illustrate that categorizing players based on preferences for single-player vs. multiplayer games may be problematic, we analysed millions of posts in Reddit for single-player and multiplayer games to see which players use more extroversion (pro-social) words, citing research suggesting that those who prefer multiplayer games should use more extroversion words. We found no noticeable differences between the two groups, although unexpectedly single-player gamers did use more extroversion words in a statistically significant manner. Ultimately, we offer caution that categorization of games and gamers – although useful at times – can oversimplify assumed preferences and, when not critically examined, may lead to the reification of misleading and exclusionary categories of both games and the people who play them.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it