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Record W1812877266 · doi:10.1504/ijkbd.2015.071469

A policy analysis of digital strategies: Brisbane vs. Vancouver

2015· article· en· W1812877266 on OpenAlexaboutno aff
Tooran Alizadeh

Bibliographic record

VenueInternational Journal of Knowledge-Based Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDigital economyRegional scienceBusinessEconomyPolitical scienceGeographyEconomics

Abstract

fetched live from OpenAlex

A growing number of cities around the world have now realised the need to strategically capitalise on the rapidly growing digital economy. In mid-2013, cities of Brisbane, Australia and Vancouver, Canada both released their 'Digital Strategy' documents to strengthen their economy by enhancing digital connections amongst citizens, business, and the whole city as a digital organisation. The paper critically investigates the digital strategies developed for the two cities to understand how they utilise the potentials of the digital economy in their respected cities and regions. The results identify fundamental differences in the two documents' core focus that firstly define different roles for the digital strategies in Brisbane vs. Vancouver, and secondly could highly affect the implications of the strategies for the two cities' overall economic development. Nevertheless, both Vancouver and Brisbane are still in the early days of implementing their digital strategies, and the paper has to be understood as a prelude to further empirical investigation.

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)0.006
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 score0.148
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0100.004
Scholarly communication0.0130.002
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.042
GPT teacher head0.364
Teacher spread0.322 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

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