The Booze Cruise: Impaired Driving in Virtual Spaces
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
In January 2007, the University of Calgary offered the first Canadian course in Serious Game Development.1,2 Computer Science 701.03 was officially a high-level graduate course, but it included participants from the arts and interdisciplinary studies at senior undergraduate levels. The course evaluation was based on a game project. The class selected a simulation of impaired driving, and called it the Booze Cruise. Before embarking on the simulation, we consulted with the Calgary Police Service. Its alcohol unit was keen to help and gave a summary of the what and why of accident types related to alcohol consumption. Impaired driving is a serious problem and a preventable cause of death and injury. Private and public health organizations are always seeking better ways to reach the public with the message that drinking and driving is dangerous and socially irresponsible. When we announced the game in October 2007, the media response was huge (see Figure 1). The game also won the best student game and people's choice categories in the FuturePlay 2007 Conference's games competition that year (www. futureplay.org). In this article, we summarize the game's design process and development stages. We also look at media responses, which are still active.
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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