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
Andri Gerber: You are a sociologist working on a wide array of topics, ranging from architecture to urban design, and more recently, on religion.It seems that the subject of video games is still not heavily researched in sociology, or at least many bemoan the scarce literature in this field.Silke Steets: There have been some interesting insights into how "games" in general can be described sociologically.This was done, for example, by Canadian-American sociologist Erving Goffman in his book Encounters.Two Studies in the Sociology of Interaction (1961).Goffman, among others, reflects upon the difference between the sphere of everyday life and the sphere of games.Both are characterized by a specific state of mind: Whereas we have a pragmatic interest in "surviving" in the sphere of everyday life, we can strip off that "seriousness" in the sphere of games.Still, and somehow paradoxically, games need to be taken seriously, in order to create their own immersive world.Another example from the sociology of games is the notion of "gamification," which presents investigations into how games and competitions have been applied as neoliberal strategies within the framework of our economic system and structures.Gerber: You recently published a great book, Der sinnhafte Auf bau der gebauten Welt (2015), in which you consider architectural objects as "social realities," following and seemingly inverting the theories of Peter Ludwig Berger (1929-2017), Thomas Luckmann (1927-2016), and George Herbert Mead (1863-1931), among others.When we consider architecture in video games, it is supposed to mimic reality, but in doing so, it is obviously a construction.My first question is in relation to this topic is: How would
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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