Understanding and evaluating cooperative games
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
Cooperative design has been an integral part of many games. With the success of games like Left4Dead, many game designers and producers are currently exploring the addition of cooperative patterns within their games. Unfortunately, very little research investigated cooperative patterns or methods to evaluate them. In this paper, we present a set of cooperative patterns identified based on analysis of fourteen cooperative games. Additionally, we propose Cooperative Performance Metrics (CPM). To evaluate the use of these CPMs, we ran a study with a total of 60 participants, grouped in 2-3 participants per session. Participants were asked to play four cooperative games (Rock Band 2, Lego Star Wars, Kameo, and Little Big Planet). Videos of the play sessions were annotated using the CPMs, which were then mapped to cooperative patterns that caused them. Results, validated through inter-rater agreement, identify several effective cooperative patterns and lessons for future cooperative game designs.
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