Part I — Introduction: Social Physics and the VESPACE Project
Bibliographic record
Abstract
This article introduces the VESPACE project, an international, multi-disciplinary digital humanities initiative to build a computer-mediated playable simulation—a video game—of the eighteenth-century Paris Fair theatre. As part of this project, a weeklong postgraduate workshop was convened by the authors in May 2020 to develop protocols and procedures for coding literary and historical data for the Ensemble social physics engine that will govern behaviour of NPCs in the interactive model. This article lays out the history and theory of social physics, the potential impacts of this project on historiographic practice, and the methodology and outcomes of the workshop week. We conclude with a discussion of lessons learned and promising leads with respect to the future of applying social physics to humanities research. [This article is part of the collection Computer Modelling and Simulation for Literary-Historical Research: VESPACE and Social Physics.]Cet article présente le projet VESPACE, une initiative pluridisciplinaire internationale dans le domaine des humanités numériques qui vise à construire une simulation ludique – un jeu vidéo – basée sur le Théâtre de Foire parisien au XVIIIe siècle. En mai 2020, les auteurs de cet article organisèrent un atelier postdoctoral d’une semainedans le but de développer des protocoles et des procédures de codage de données littéraires et historiques pour le moteur de physique sociale Ensemble, qui règle le comportement des personnages non joueurs (PNJ) dans le modèle interactif. Cet article présente l’histoire et la théorie de la physique sociale, les impacts potentiels de ce projet sur la pratique historiographique, ainsi que la méthodologie et les résultats de la semaine d’atelier. Nous concluons par une discussion des leçons apprises et des perspectives prometteuses pour l’avenir de l’application de la physique sociale dans la recherche en sciences humaines. [Cet article fait partie de la collection Modélisation et simulation informatiques pour la recherche littéraire-historique : VESPACE et physique sociale.]
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".