Alternate Reality Game and Culural Heritage: The “Aequilibrium” Project
Bibliographic record
Abstract
"Aequilibrium" is a transmedia and location-based experience which engages players in an adventure that blurs the boundaries between digital and physical spaces, imaginary and real people from the local community. The project is the first Italian Alternate Reality Game (ARG) dedicated to Leonardo Da Vinci and is aimed at promoting the territory of Lomellina adopting innovative communication strategies to engage players in a game which is designed to amuse and encourage tourism. The transmedia and the locative experience were designed by a team of researchers from the Politecnico di Torino and Guglielmo Marconi University. Starting from the analysis of the Aequilibrium project, this essay focuses on how alternate reality games can promote participation in cultural experiences which offer cultural activators fostering collaboration and creative grassroots production within communities of players. «Aequilibrium» est une expérience transmédias basée sur l'emplacement qui entraîne les joueurs dans une aventure qui brouille la distinction entre les espaces numériques et physiques ainsi que les personnes imaginaires et réelles de la communauté locale. Le projet est le premier jeu de réalité alternative italien dédié à Léonard de Vinci et dont le but est de promouvoir le territoire de Lomellina, en adoptant des stratégies de communication qui font participer les joueurs à un jeu conçu pour les amuser et encourager le tourisme. L'expérience transmédias et locative a été conçue par une équipe de chercheurs de l'université Politecnico di Torino et Guglielmo Marconi. À partir d'une analyse du projet Aequilibrium, cet essai met l'accent sur la façon dont les jeux de réalité alternative peuvent promouvoir la participation à des expériences culturelles qui offrent des activateurs culturels, favorisant la collaboration et la production créative populaire au sein des communautés de joueurs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".