An “Alternative to the Pen”? Perspectives for the Design of Historiographical Videogames
Bibliographic record
Abstract
This article presents how the tools of videogame design can be used to convey historical arguments, and to what extent historians could benefit from creating such videogames. We begin by positioning our argument within the literature on the writing of history, linking it to formal and writing issues, which leads us to delve into various definitions of what “videogames for history” could be, and what operational frameworks could be derived from those definitions. We then confront some key principles of design to a selection of actual videogame projects to discuss the possibility of “historiographical game design” to be considered as “an alternative to the pen” (Chapman, 2013, p. 329) for historians. Our goal is to identify general principles in the design of historiographical videogames, to provide an improved and refined definition of these games from a design perspective and to formulate general guidelines to inform further explorations through research-creation projects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".