Bibliographic record
Abstract
Modern society is mediated by social infrastructure.Basketball hoops tender play as social lubricant, playgrounds afford the respite of adult conversation among parents, while a park bench makes possible chance encounters.Eric Klinenburg in his book Palaces for the People defines "social infrastructure" as "the physical places and organizations that shape the way people interact" [Klinenburg 2018, p. 5].Alongside our mores, social infrastructure not only supports our need to connect but inspires us to do so, providing a blueprint that helps shape the worlds we inhabit while shaping the people that we become within them.The advent of modern video games in the '70s and '80s created new avenues for play-infused infrastructure.Video arcades cultivated bonding and relationship building, giving rise to their own social norms and rites of inclusion.Though entertaining on their own, video games served as a "social MacGuffin" in the nexus of these arcades; like board games, they provided a reason to not just gather but linger.As a testament to this, one of the earliest home consoles, the Magnavox Odyssey, was envisioned partly as a board game, including a playmat and tokens along with the hardware.This early history helps highlight a critical transformation as we have moved online and increased the fidelity of gaming experiences.Today video games transcend physical distance, drawing people together around the promise of play and providing a shared purpose that helps in fostering bonds across cultures.Where once video games merely served as the toys of our social parlours, today these digital worlds now function directly as habitable infrastructure.In short, video games have become the very social parlour itself.The concept of video games as social infrastructure is profound.The shift necessitates a fundamental change in how we think about games as a society.It befits us to take greater responsibility in the games we create and their impact on players and communities.Building a game that others
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".