How computer gamers experience the game situation
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
Very little is known about computer gamers' playing experience. Most social scientific research has treated gaming as an undifferentiated activity associated with various factors outside the gaming context. This article considers computer games as behavior settings worthy of social scientific investigation in their own right and contributes to a better understanding of computer gaming as a complex, context-dependent, goal-directed activity. The results of an exploratory interview-based study of computer gaming within the "first-person shooter" (FPS) game genre are reported. FPS gaming is a fast-paced form of goal-directed activity that takes place in complex, dynamic behavioral environments where players must quickly make sense of changes in their immediate situation and respond with appropriate actions. Gamers' perceptions and evaluations of various aspects of the FPS gaming situation are documented, including positive and negative aspects of game interfaces, map environments, weapons, computer-generated game characters (bots), multiplayer gaming on local area networks (LANs) or the internet, and single player gaming. The results provide insights into the structure of gamers' mental models of the FPS genre by identifying salient categories of their FPS gaming experience. It is proposed that aspects of FPS games most salient to gamers were those perceived to be most behaviorally relevant to goal attainment, and that the evaluation of various situational stimuli depended on the extent to which they were perceived either to support or to hinder goal attainment. Implications for the design of FPS games that players experience as challenging, interesting, and fun are discussed.
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) | 0.000 | 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