Gaming the Publishing Industry: Exploring Diverse Open Scholarship Models in Digital Games Studies
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
The emergent field of digital game scholarship has developed along unique communicative lines, illuminating alternative models and diversified potentials for scholarly communication. Following the decline of print-based magazine journalism, the rise of moderated aggregator sites, such as Kotaku, Polygon, and Rock Paper Shotgun has exposed many independent voices to larger audiences. Much of the scholarship cited in current academic work can be found online at sites like Critical Distance (which uses “roundups, roundtables, podcasts, and critical compilations” to encourage dialogue between “developers, critics, educators and enthusiasts”), First Person Scholar, a middle-state publication that combines “the timeliness and succinctness of a blog, while retaining the rigor and context of a conventional journal article” (Hawreliak), highly polished and curated online zines such as Heterotopias, and from quality video bloggers such as Noah Caldwell Gervais and short-form documentary creators such as Gvmers. These heterogeneous alternatives collectively model a publishing plasticity and adaptiveness, establishing a culture of open scholarship practices, inclusive and diverse voices, and a rapid deployment of ideas and perspectives. This paper argues that emergent models of scholarly communication explored by the game studies community include but also moderate the reactive energies of social media and the toxicity of “gamer” culture.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.017 | 0.043 |
| Open science | 0.004 | 0.004 |
| 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 it