Outbreak: Lessons Learned from Developing a “History Game”
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
This paper describes the production of Outbreak, a game focused on the 1885 smallpox epidemic in Montreal. It is a preliminary report on the manner in which, by both theorizing about and building a game, we are responding to some of the questions that have animated the literature on computer games for history. The article begins with a survey of publications by researchers who have studied the capacity of games to support learning, and outlined how these can be used in concert with books and other media. We next provide the context to our project, which was conceived to market a film to be broadcast on television, and support a book on which the film was based – a bestselling history of a preventable tragedy that resulted in the deaths of over 3,000 Montrealers. We outline how we built from the book, creating a game that asked the player to save as many as possible from death, using tools that mimicked that which was available in the late nineteenth century. We conclude by reflecting on the lessons that we learned, and how we will apply these to our present and future projects.
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) | 0.002 | 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