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Record W2057757383 · doi:10.1177/1748048513491893

Reflexive design of the recursive space of virtual worlds

2013· article· en· W2057757383 on OpenAlexaff
David Harris Smith

Bibliographic record

VenueInternational Communication Gazette · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsMcMaster University
Fundersnot available
KeywordsReflexivityUrbanismArticulation (sociology)SociologyMetaverseIntersection (aeronautics)Embodied cognitionSpace (punctuation)EpistemologyArchitectureVirtual realityAestheticsComputer scienceVisual artsSocial sciencePolitical scienceHuman–computer interactionArtEngineering

Abstract

fetched live from OpenAlex

This article considers the intersection of urbanism and digital culture to theorize a model of mediated urbanism and its application to a designed virtual world for artistic and scientific collaboration. Historical precedents informing the current research include artist networks of the late 1960s and early 1970s that sought to bridge and democratize scientific, technological, and artistic endeavors. The author proposes that mediated urbanism in the reflexive recursive space of virtual worlds references and reworks embodied forms of urbanism and fosters the development of new urbanite forums. The awareness of the nature and history of this articulation may be productively used to inform the design of these emerging virtual forums of knowledge production and artistic creation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.014
Scholarly communication0.0090.010
Open science0.0020.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.047
GPT teacher head0.258
Teacher spread0.211 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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