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Record W4377027861 · doi:10.1177/15356841231173644

Scoreboard Urbanism: Theorizing Mental Life in the Digitally Mediated Metropolis

2023· article· en· W4377027861 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCity and Community · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Mobility and Location-Based Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUrbanismRealmPhenomenonAestheticsSociologyPsychologyEpistemologyPolitical scienceVisual artsArtLawArchitecturePhilosophy

Abstract

fetched live from OpenAlex

Georg Simmel famously argued that the sensory onslaught of the urban environment forces people to reduce the world to calculable quantities over colorful qualities and adopt a blasé attitude of muted emotions. Today’s digitally mediated city involves levels of quantification that Simmel could have scarcely imagined. However, rather than exacerbating the blasé attitude, this paper makes the case that digital technologies potentially increase our emotional and moral attachments to the urban environment—a phenomenon that can be called “scoreboard urbanism.” From Yelp ratings to Fitbit step scores, our relationship to the city is increasingly mediated by quantitative metrics. The purpose of this paper is to outline the basic characteristics of scoreboard urbanism as a distinct mode of life that entails new ways of perceiving and interacting with the urban public realm. In doing so, the paper argues that this phenomenon has transformed the city into a “gamespace” characterized by the competitive and exhilarating drive to score points.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.323
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it