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Enregistrement W1528029253

Ten Minutes Wide: Human Walking Capacities and the Experiential Quality of Campus Design.

2011· article· en· W1528029253 sur OpenAlexaboutno aff
David L. Spooner

Notice bibliographique

RevuePlanning for higher education · 2011
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueUrban Transport and Accessibility
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMileMetropolitan areaQuarter (Canadian coin)PopulationTRIPS architectureDestinationsSociologyTransport engineeringGeographyDemographyEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Designing for Human Capacities All humans have limits based on their physical abilities. Collectively, these human capacities inform whether or not the built environment fits our needs (Ittelson et al. 1974). For example, the human capacity to walk at an average speed of to three miles per hour limits the distance a person can travel in a given period of time. Combining this fact with the average person's tolerance for walking in terms of distance and time suggests that the best fit occurs when likely destinations in the built environment fall within a quarter-mile radius or a 10-minute walk. Research has shown that this distance complies with human scale; this particular human capacity has informed the design of cities and communities worldwide (Barnett 2003; Calthorpe 1993; Perry 1929). A tangential idea related to the quarter-mile or 10-minute walk is referred to as the Marchetti constant. The Marchetti constant states that throughout history, the time people spend traveling each day has remained at a fairly constant and a half hours (Marchetti 1994), and, on average, people prefer to travel no more than half an hour on trips to and from home (Newman and Jennings 2008). These two human capacities effectively prescribe that the built environment should be approximately one hour wide, where the average one-way commute, regardless of transportation type, equals 30 minutes. In most of today's autocentric urban environments, a 30-minute commute would be a welcome relief! For example, in metropolitan Atlanta, 11.8 percent of the population (approximately half a million people) spends over an hour commuting way to work (Hart 2006). The point is that while we can figure out the maximums and minimums to fit human capacities, our built environments do not always coincide with these limits. Evidence of this is seen in all types of built environments, and college campuses are no exception. In an academic setting, the travel-time budget is quite different. The one hour wide urban planning ideal shrinks to 10 minutes wide, given the fact that students have a set amount of time to change classes. Based on a 10-minute intersession and our physical walking abilities, the maximum distance between classes should be at most 2,400 feet and fit within a quarter-mile radius. However, the form and spatial configuration of many campuses has shifted to a suburban model, in which distances between buildings are scaled to fit the automobile and often exceed the dimensions dictated by human walking capacities (Kenney, Dumont, and Kenney 2005). Beginning in the 1960s, campus master plans addressed this shift in scale by designing for human users and placing likely destinations within a quarter-mile radius. Today, many master plans go a step further and actually promote the experiential characteristics associated with campus walkability as an important way to recruit students and bring feelings of community to the campus setting (see the 2008 campus master plans for Middlebury College and the University of Utah [web addresses for these and all plans cited are included at the end of the article]). Thus, whether a campus is large or small, the idea of a 10-minute walk is an important human-scaled design standard that affects an institution in significant ways beyond just getting students to class on time. Designing a 10-Minute Walk Designing a 10-minute walk seems like a simple exercise. Based on earlier information, all needs to do is provide a walking surface and make it approximately 2,400 feet long. But in reality, this is a much more complex design problem. Beyond answering the question of why a 10-minute walk is important, many master plans fail to suggest how to effectively create one. Keeping human capacities in mind, what would such a walk look like and how should it function? To begin answering this question, the author reviewed 37 campus master plans and categorized all stated design goals for walking paths into three main categories: (1) functional, (2) aesthetic, and (3) experiential. …

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)0,013
Version: metacan-v3-hybrid-931329e0061cStatut 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: aucune
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,024

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,013
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,011
Communication savante0,0070,006
Science ouverte0,0010,006
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0070,000

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 Opus0,125
Tête enseignante GPT0,377
Écart entre enseignants0,252 · 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'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

Citations3
Publié2011
Routes d'admission1
Résumé présentoui

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