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Record W3113541463 · doi:10.29173/irie264

The cybercity as a medium Public living and agency in the digitally shaped urban space

2010· article· en· W3113541463 on OpenAlexvenueno aff
Seija Ridell

Bibliographic record

VenueThe International Review of Information Ethics · 2010
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Public spaceConsolidation (business)Space (punctuation)Unconscious mindSociologyPublic relationsIntersection (aeronautics)Political scienceMedia studiesAestheticsEngineeringArchitectural engineeringBusinessSocial scienceComputer scienceEpistemologyArtTransport engineering

Abstract

fetched live from OpenAlex

The digitalized urban environment is explored in the paper as a medium with several overlapping and interweaving spatial layers. The author suggests that it has grown increasingly complex in the multi-spaced and multiply scaled cybercities for people to share in public space. Moreover, the challenges of public living in contemporary urban settings emerge most intensely at the points of intersection of the invisible technostructure and the (mass) media saturated phenomenality of the city. At these intersections, one ethically and politically burning issue is how people through their ICT-related activities contribute to the ?automatic production of space‘. More specifically, critical attention should be paid to people‘s active, but not necessarily selfreflexive, participation in the consolidation of the ?technological unconscious‘ that conditions their own public agency.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.019
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.050
Scholarly communication0.0190.016
Open science0.0010.011
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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