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 goal of this article is to discuss how digital war games such as the Call of Duty series elicit consent for the U.S. military, militarism and the wars waged by the U.S. and its allies abroad. Building bridges between the humanities approach to Game Studies, American Studies, International Relations and Critical Geopolitics, we start from the assumption that digital games are more than “kid’s games”; they are sophisticated vehicles inhabiting and disseminating specific ideologies (Leonard 2004). Accordingly, our goal is to conduct a content analysis (Sisler 2008) of Call of Duty 4: Modern Warfare and Call of Duty: Modern Warfare 2 to show how these games contain images and narratives that (1) resonate with and reinforce a tabloid imaginary of post-9/11 geopolitics (Debrix 2008); (2) glorify military power and elicit consent for the idea that state violence and wars are inevitable; and (3) encourage our myopia by depicting a sanitized vision of war and downplaying the negative consequences of state violence (Stahl 2006). The conclusion invites players to think about ways to criticize the way games like Call of Duty employ and deploy values that (re)write the militarist mindset that has often pervaded the post-9/11 U.S. national security debate.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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