Temporary Break or Permanent Departure? Rethinking What It Means to Quit <i>EVE Online</i>
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
To date, much of the research about massively multiplayer online games (MMOGs) and the people who play them has focused on studies of current players. Comparatively, little is known about why players quit. Rather than assuming MMOG play begins and ends with personal interest, this article uses a leisure studies framework to account for barriers and participation to play. Drawing on survey responses from 133 former EVE Online players, this article demonstrates that quitting is not a strict binary where one moves from playing to not playing. Furthermore, quitting in the context of MMOGs is not always a definitive act as some players will leave and then return to a particular game numerous times. Ultimately, this article argues that the voices of former players are an underattended demographic that can add further insights allowing game scholars to better understand why players gravitate toward particular games and not others.
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 | 0.000 | 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 | 0.001 | 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