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Enregistrement W646754425

2028: Real estate development strategies towards a successful Olympic legacy

2010· article· en· W646754425 sur OpenAlexaboutno aff
E.E.J.F.M. Van Prooye

Notice bibliographique

RevueResearch Repository (Delft University of Technology) · 2010
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSport and Mega-Event Impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOlympiadGovernment (linguistics)DreamPolitical scienceOrder (exchange)Public administrationOperations researchHistoryBusinessEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Since the 2000 Olympics in Sydney, where the Dutch Olympians won a record amount of Olympic medals, the Olympic Dream has yet again awoken in the Netherlands. The dream to stage the Olympic once again, exactly 100 years after the first and only Olympiad in the Netherlands, was aimed at 2028. So why would the Netherlands want to host such an event? And how show they tackle the assignment? After the Olympiad in Athens in 2004, the Dutch Olympic dream had gained enough support to establish a concrete movement. This was done by establishing the ‘Alliantie’, a collaboration between the Dutch Olympic Committee, the NOC*NSF, the national government, the provincial government and the municipalities of the four largest cities in the Netherlands. The ‘Alliantie’ were to lead the exploratory studies of the Olympic assignment in the Netherlands. This finally led to the ‘Olympisch Plan 2028’, a report which included the ambitions, challenges, strategies and future circumstances of the potential Olympic assignment in the Netherlands. Eight ambitions were distinguished, of which the ambition that will have the most dominant stamp in the Netherlands, is the spatial ambition. In this ambition branch the ‘Alliantie’ initiated a single workshop study in order to explore the spatial assignment the Olympics would impose in the Netherlands. This study provided the basic framework and information for numerous studies to follow. One of which is the study Deloitte and NIROV have conducted on the Dutch stakeholders’ willingness to invest in Olympic developments. This is where this research comes into play; how did former host cities tackle the Olympic assignment? First of all, a superficial scan was made of former hosts and Olympic researches. Quickly the conclusion was reached that the Olympic developments in a city do not always bring the supposed successes and increase in quality. In many cases the Olympic developments were not used, under used of not used correctly. This created so called ‘white elephants’, large venues and facilities that cost more money than they provide, which inevitably lead to high debts. Major international cities like Melbourne, Montreal, Sydney and Athens, were not able to coop with the developments after the Olympic circus had left town. So how could a small nation like the Netherlands be successful were other great nations and cities could not? Thus the second problem can be distinguished; how to fit the Olympic assignment in the Netherlands, especially the building left behind, the legacy. Therefore the following problem statement was made: Due to the lack of sufficient attention to the long-term objectives for the post- Olympic real estate, undesired ‘white elephants’ arise from the Olympic real estate legacy in the former host cities. What is legacy exactly, and how is it created? These question were the next step in identifying the problem. Legacy can be identified in two categories, tangible or hard legacy, and intangible or soft legacy. Soft legacy can be described as the values, the knowledge, the memories and the general Olympic thought the Olympiad provides the host city. Hard legacy is the architecture, the infrastructure and the economic impact the Olympics leave behind. However a conference held in 2003 discussing the term legacy and what role it can play in Olympic cities, came to the conclusion that legacy is multidisciplinary and dynamic and is affected by a variety of local and global factors’. Therefore legacy creation is unique is every single city and location, and it is thus difficult to make a general definition. The Olympic development process plays an important role in answering the question on how legacy is created. The process consists of three phases; the initiatory and bidding phase, theorganisation and realisation phase and the post-Olympic phase. How does legacy creation fit into this process? To answer the latter question, a conceptual model was made on what influences legacy. Indirectly the before distinguished local factors play a significant role. The traditional planning culture of a nation, region or city determines the possibilities and opportunities of Olympic developments. Directly, the used development structure that is used to accomplish the Olympic assignment, plays an even larger role, as it includes all the pieces of the puzzle that are needed for the creation of the Olympic developments. The aspects that have been identified to the development structure are the initiative, objectives, stakeholders, organisational structure, budget, financial structure and the interferences. In addition the consequences, i.e. legacy, of the compilation of these different aspects is also of importance to learn lessons from former Olympic host cities. In turn, within the development structure aspects a division can be made between characteristics on four different sustainable development ambition levels; the governance, social , spatial and economical level. The objectives, strategies and legacies all have different perspectives which include all the different levels. This entire process then produced the following research question; Which development structure1 has the greatest potential concerning legacy1 for an edition of the Olympic Games in the Netherlands in 2028?

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,060

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0060,003
Communication savante0,0100,006
Science ouverte0,0020,011
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0180,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,036
Tête enseignante GPT0,340
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2010
Routes d'admission1
Résumé présentoui

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