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Portfolio of Major Events in Auckland, Wellington and Dunedin

2019· book-chapter· en· W3016372422 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGoodfellow Publishers eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTourismGeographyPortfolioChristian ministryPopulationPoliticsRegional sciencePolitical scienceEconomic growthEconomyBusinessSociologyFinanceEconomicsDemography

Abstract

fetched live from OpenAlex

The overall purpose of this chapter is to analyse the inter-relations between institutional arrangements, event policy frameworks and applied portfolio approaches. The chapter aims to explore the influence of the public sector institutional and policy environments on the realisation of portfolio approaches in three cities in New Zealand, Auckland, Wellington and Dunedin. The cities have a core national status (Ministry of Business Innovation and Employment, 2012) in terms of economic, political and socio-cultural share, and represent a variety of different contexts. Auckland is located in the North Island of New Zealand. It is the largest urban area in the country with a population of 1,415,500. It contains around 190 ethnic groups. Auckland is New Zealand’s principle business centre and accounts for 35.3% of New Zealand’s GDP as major national gateway for imports and exports (Statistics New Zealand, 2014). It is the most visited tourist destination in New Zealand, attracting around 70% of all visitors to the country (aucklandnz.com, n.d.). Auckland has been recognised in different international comparative studies such as Mercer Quality of Living Survey is 2015 and 2018, where it was ranked the third most liveable city in the world (Mercer, 2015, 2018).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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