Report on ReAnimate'24: 2024 Summer School on Retro Gaming History, Critic, and Development
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
For many years, there has been an interest in ''old'' games, either real old games or recent games with an ''old'' look and feel. The retro gaming community has grown from very niche to mainstream, following the general gaming trend. Retro gaming has also entered the general psyche with books, movies, documentaries, articles, etc. becoming mainstream. However, despite this mainstream status and some recent books, retro gaming remains under-studied in academia and existing research rarely enters mass media. We proposed a summer school dedicated to retro gaming, which invited both the humanities and engineering fields to provide unique insights on retro gaming, both theoretical and practical, and opportunities for cross-fertilization among research fields. This summer school welcomed anyone interested in retro gaming. In particular, students in the humanities learned about general game development and the particularities of retro games while students in engineering learned about the history of gaming and theories about games and game design. This summer school, supported by the ACM SIGSOFT and Cloanto, featured lectures in the mornings and practical, hands-on sessions in the afternoon given by experts on (retro) games as well as site visits, panels, and discussions to foster exchanges, create a community, and promote the studies of retro games.
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 | 0.139 |
| 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) | 0.000 | 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