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Record W7008155264

Authenticity-in-Context: Embedding the Arts and Culture in Branding Berlin and Singapore

2009· other· en· W7008155264 on OpenAlexaff

Bibliographic record

VenueOpenArchive@CBS (Copenhagen Business School) · 2009
Typeother
Languageen
Field
Topic
Canadian institutionsBrandon University
Fundersnot available
KeywordsPlace brandingThe artsOrder (exchange)Nation brandingPoliticsCreative industries
DOInot available

Abstract

fetched live from OpenAlex

This paper compares the branding strategies of Berlin and Singapore. The respective authorities in these cities are actively marketing, branding and transforming their cities, so that these locations will be perceived as culturally vibrant, technologically advanced and attractive for investors, tourists and creative workers. While Berlin and Singapore share the same goals, they also share similar problems – how can they convince a world that is critical and cynical about the commercial images presented through their place brands? How can they convince the world that their cities are really exciting and truly creative? The arts and culture – both popular and high – are used in place branding to address some of these challenges. This paper also concludes that place branding and its authenticity must be understood in context. The emerging reality of the place means that the brand should also reflect the local entangled social, economic and political issues; the brand, in order to be authentic, should also communicate the commercial and the vision of the place.

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)0.002
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0100.006
Open science0.0010.009
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 head0.015
GPT teacher head0.276
Teacher spread0.262 · 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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