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
Whether they are made to entertain you, or to educate you, good video games engage you. Significant research has tried to understand engagement in games by measuring player experience (PX). Traditionally, PX evaluation has focused on the enjoyment of game, or the motivation of players; these factors no doubt contribute to engagement, but do decisions regarding play environment (e.g., the choice of game controller) affect the player more deeply than that? We apply self-determination theory (specifically satisfaction of needs and self-discrepancy represented using the five factors model of personality) to explain PX in an experiment with controller type as the manipulation. Our study shows that there are a number of effects of controller on PX and in-game player personality. These findings provide both a lens with which to view controller effects in games and a guide for controller choice in the design of new games. Our research demonstrates that including self-characteristics assessment in the PX evaluation toolbox is valuable and useful for understanding player experience.
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) | 0.031 | 0.019 |
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