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Record W3164525002 · doi:10.1080/17510694.2021.1912536

Art toy as a tool for engaging the global public on the city of Surabaya

2021· article· en· W3164525002 on OpenAlexfundno aff
Aristarchus Pranayama Kuntjara

Bibliographic record

VenueCreative Industries Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsSymbol (formal)Character (mathematics)EmblemTourismPublic diplomacyAdvertisingGlobal cityMarketingSociologyResource (disambiguation)Visual artsBusinessPublic relationsPolitical scienceDiplomacyComputer scienceArtLaw

Abstract

fetched live from OpenAlex

Art toys, often called designer toys, are three-dimensional figures of hybrid and stylised characters that are reproduced and commonly customised in limited quantities and sold among segmented hobbyists and collectors. Within this niche, however, there is an unexplored territory of art toy character design that is based on a city’s symbols. Such is the case with the city emblem of Surabaya, Indonesia, which already has the iconic images of a shark and a crocodile (Suro and Boyo). As Surabaya continuously focuses on its image, art toys based on the city’s symbols prove to be a potential platform and asset for engaging the public towards the city. If aligned and integrated well with tourism activities, licensing, branding, and various marketing communication media, it is a prospective resource and intellectual property for the city’s public diplomacy in local and global settings. This article traces and conveys the design process and investigates the possibilities and concerns of designing and promoting an art toy platform character named Subo, based on Surabaya’s city symbol.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.004
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0010.001
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 head0.138
GPT teacher head0.343
Teacher spread0.204 · 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 designNot applicable
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

Citations3
Published2021
Admission routes1
Has abstractyes

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