Bibliographic record
Abstract
Video game playing is becoming a predominant part of popular culture. Games, like Assassin’s Creed (Ubisoft, released 2007), The Sims (Maxis, released 2000), Guitar Hero (RedOctane, released 2005), and World of War Craft (Bilizzard, released 2004), have attracted players from many different cultures and age groups. In this paper, we propose that the experience of playing a video game, like Assassin’s Creed, is a personal experience shaped through one’s emotional values, expectations, knowledge, and attitudes as influenced by culture. As we set out to review the Assassin’s Creed game, we discovered that each one of us had a different experience with the game. In this paper, we draw on our Assassin’s Creed play sessions. This experience is shaped by our different cultural viewpoints, including Middle-Eastern and Western, as well as intellectual disciplinary backgrounds, which include architecture, theatre, and computer science. To Maha and Magy, for example, the game aroused many nostalgic feelings through its simulated Middle-Eastern cities, the use of Arabic words, accents and gestures, and the detailed Middle-Eastern architectural design. While such small details meant much when viewed by Maha and Magy, their values were different when viewed by Simon and David. To both Simon and David, the game play experience was heightened through the beautiful architectural detail and the use of the environment layout as a function of gameplay, such as the use of rooftops for platforming, fast movement and flying-like actions, and stealth. This collaborative game review suggests that a game is, in interesting ways, experienced and perceived differently by players from divergent cultural-linguistic situations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".