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Enregistrement W2593466003 · doi:10.1201/9781315116068-27

Real estate, residency, design and sustainability: Reconsidering innovation and efficacy in development

2017· article· en· W2593466003 sur OpenAlexaboutno aff
Sancho Rajan, B.R. Sinclair

Notice bibliographique

RevueThe 10th EAAE/ARCC International Conference · 2017
Typearticle
Langueen
DomaineEngineering
ThématiqueSustainable Building Design and Assessment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésReal estateSharing economyRentingBusinessFunction (biology)MarketingEconomicsFinancePolitical scienceLaw

Résumé

récupéré en direct d'OpenAlex

Real estate planning, design, development and building prove deeply complex. For nearly five decades developers have been doubling down, contractors have been cutting corners, architects and engineers have been copying and pasting, planners have been creating more rules, and bankers, lawyers, realtors and insurers have all profited excessively from a fundamentally broken system (Miller 2009). All the while, home owners have unknowingly and knowingly spent trillions of dollars on accommodation that lacks in either quality, cost, location, fit or all of the above. However, as long as the economy continues on an upward trajectory, the climate doesn’t change too much and home buyers don’t ask for anything more, the system will endure. Should we be changing anything? Homes shape our communities, guide our relationships, characterize our identity, create intimacy and increasingly prove vehicles for funding retirement. Since 2008, average home prices have risen by 50% pushing family net worth up 44.5% (Marr 2015). The real estate, rental and leasing economy is equivalent in size to the educational services and healthcare industries combined and nearly 20 times larger than the arts, entertainment and recreation industries (Statistics Canada 2015). The housing sector is a life line to the economy and, if thrown off balance, has proven to be crippling. We remain dependent on a fragile system which, in many ways, doesn’t function as well as we think or as well as we desire. Today, 20% of Canadians face an affordable housing crisis, spending over half their income on their home (McMahon 2015). This problem is magnified globally, where an estimated 1.6 billion will be affected by an affordable housing crisis by 2025 (Woetzel 2014). Rising prices and lack of productivity within the construction industry contribute to unaffordability (LePatner & Jacobson 2007). This is intensified by a lack of innovation; only one construction and engineering company made it to Forbes 100 most innovative companies in 2014. Since the turn of the 19th century, the movement of architects and engineers from a craft practice model to a professional services model shifted liability onto developers and withdrew the creativity involved in place-making by creating a highly fragmented and arguably dysfunctional industry. As such, less than 5% of homes have an architect involved in the design (Brown & North 2011). The housing industry is also a great environmental concern. Buildings contribute to one third of global greenhouse gas emissions (Huovila 2009) and the urban sprawl of the last few decades has resulted in numerous negative externalities (Thompson 2013). We cannot continue to rely on this broken system. Although new urban and minimalistic movements are becoming more prominent, a systemic change is needed (Zevon 2011). Purchasers should no longer forgo quality, cost, location or fit. By unveiling the venality of the current industry, and finding the cruxes for change, we can create a more innovative and integrative industry. The present research critically considers the status quo, exploring aspects of the design and development industries that desperately need overhaul, integration, coordination and stream-lining. Holistic conceptual frameworks can be shaped and applied to tackle the daunting complexity of such systems (Sinclair 2009). To such ends the authors present a model for systemic reform that aims to shift priorities from profit and bottom-line thinking to place-making and quality of life, understanding that creativity, balance and reform are urgently required in order to see real progress in an endemically fragmented & problematic ethos.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,714
Score d'incertitude au seuil0,507

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,067
Tête enseignante GPT0,313
Écart entre enseignants0,246 · 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 tête enseignante, pas un consensus.

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

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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