Historic preservation in Nazi Germany: place, memory, and nationalism

While numerous studies have examined the post-war contestation surrounding commemorative sites associated with the legacy of Nazi Germany, relatively little attention has been dedicated to the ways in which the Nazi regime itself sought to create places of memory congruent with the movement's political and cultural goals. Indeed, party leaders sponsored a variety of disparate, and at times contradictory, programs to re-orientate some of Germany's most prominent historic places to better serve the needs of the regime. To expand our understanding of this process, this article examines the practice and rhetoric of historic preservation in Bavaria during the Nazi period with a focus on the preservationist program sponsored by Bavarian President Ludwig Siebert. Nazi propaganda promised to rejuvenate and protect Germany's architectural heritage for the public good, but the regime's actual priorities and policies led to widespread confiscation, damage, and eventually destruction.     

An officer and an activist: Futuring,precarity and life after exile in Namibia

This article explores the life histories of two Namibians who grew up in SWAPO's exile camps in Angola and their ‘futuring’ trajectories once they returned home to Namibia after independence. Presenting these actors’ life histories of navigating Namibian society helps challenge a one-sided economic interpretation of precariousness. More critical than asserting dichotomies between ‘elite’ and ‘precariat’ are the stratagems and choices shaping lived experiences.     

Challenges to Bridging Discrepant Knowledge Bases: A Case Study of the Norwegian Centre for Offshore Wind Energy

From a theoretical perspective, it is possible to enhance the innovation of firms and institutions by combining the analytic (scientific) knowledge base of research and development (R&D) institutions with the synthetic (practical) knowledge base of industries. Such combinations of knowledge are also believed to support regional development. One such initiative to bridge knowledge from the R&D sector and industry is the Norwegian Centre for Offshore Wind Energy (NORCOWE). However, as our case study shows, it is hard to bridge knowledge from these two partner groups. We found that this is mainly because of differences in the partners' timelines (long versus short), their attitudes toward knowledge (research based versus experience based), application of the knowledge (knowledge per se versus commercialization), and organizational dimensions (linear/closed process versus interactive/open process). These differences show that the knowledge bases of these two groups may not just be different; they can also be seen as discrepant. We also argue that the NORCOWE initiative is influenced by a “policy push” logic. This implies that the initiative was not properly embedded in the industrial or R&D institutions before being launched, but was instead driven by a political will to promote the development of a new renewable energy source.     

Where cities fail to triumph: The impact of urban location and local collaboration on innovation in Norway

The role of cities in fostering innovation has for long been taken for granted. Agglomeration and the knowledge spillovers generated in dense urban environments have been considered fundamental drivers of innovation. This view has, however, become challenged by research questioning the returns to physical agglomeration and local networking, placing instead more emphasis on the importance of interregional and international collaboration, and on innovation in peripheral regions. This paper delves into the debate on the role of cities for innovation by examining the interplay between urban location and local collaboration in Norway. It uses data from the Community Innovation Survey for 2006–2010 to map out the geographical dimension of R&D collaboration in Norwegian firms with a view to assessing whether different types of R&D collaboration in urban and rural locations affect firms’ propensity to innovate. The results show that local collaboration is associated with increased process and organisational innovation, while it does not produce higher levels of product or marketing innovation. Conversely, international collaboration is connected with higher probabilities of product, new-to-market and marketing innovations. Furthermore, location in urban or rural areas makes no difference for most innovation outcomes in Norway when other characteristics are controlled for. Location in cities also does not shape the returns to local R&D collaboration. Hence, the role of cities for innovation in Norway, whether in themselves or as sites for dense local interaction, is less relevant than the urban innovation literature would predict.     

A New Method of Adaptive Zoning for Spatial Interaction Models

Spatial interaction models commonly use discrete zones to represent locations. The computational requirements of the models normally arise with the square of the number of zones or worse. For computationally intensive models, such as land use–transport interaction models and activity‐based models for city regions, this dependency of zone size is a long‐standing problem that has not disappeared even with increasing computation speed in PCs—it still forces modelers to compromise on the spatial resolution and extent of model coverage as well as on the rigor and depth of model‐based analysis. This article introduces a new type of discrete zone system, with the objective of reducing the time for estimating and applying spatial interaction models while maintaining their accuracy. The premise of the new system is that the appropriate size of destination zones depends on the distance to their origin zone: at short distances, spatial accuracy is important and destination zones must be small; at longer distances, knowing the precise location becomes less important and zones can be larger. The new method defines a specific zone map for every origin zone; each origin zone becomes the focus of its own map, surrounded by small zones nearby and large zones farther away. We present the theoretical formulation of the new method and test it with a model of commuting in England. The results of the new method are equivalent to those of the conventional model, despite reducing the number of zone pairs by 96% and the computation time by 70%. Los modelos de interacción espacial suelen utilizar zonas discretas para representar áreas o puntos de interés. Los requisitos computacionales de estos modelos normalmente aumentan a razón del número de zonas elevadas al cuadrado o más. Para modelos computacionalmente intensivos como los modelos de interacción entre uso de suelo y transporte y los modelos basados en actividades para ciudades‐región, el impacto del tamaño de la zona es un problema persistente no superado aun. Esta limitación persiste a pesar de los grandes avances en la velocidad de procesamiento en computadoras, pues obliga a los modeladores a hacer concesiones entre la resolución espacial y la extensión que abarca el modelo, así como en el rigor y profundidad del análisis. En este artículo se presenta un nuevo tipo de sistema de zonas discretas que: a) tienen como objetivo reducir el tiempo de estimación de la aplicación de modelos de interacción espacial; y b) al mismo tiempo mantienen su nivel de precisión. La premisa que gobierna este nuevo sistema es que el tamaño apropiado de las zonas de destino depende de la distancia a su zona de origen: a distancias cortas, la precisión espacial es importante y las zonas de destino deben ser pequeño; a distancias mas largas, conocer la ubicación precisa es progresivamente menos importante y las zonas pueden ser mayores. El nuevo método define un mapa específico de zonas para cada zona de origen; cada zona de origen se convierte en el foco de su propio mapa, rodeada de zonas cercanas pequeñas y zonas grandes a mayor distancia. El estudio presenta la formulación teórica del nuevo método y su demostración vía un modelo de desplazamientos residencia‐trabajo en Inglaterra. Los resultados del nuevo método son equivalentes a las del modelo convencional, a pesar de reducir del número de pares de zonas en un 96% y el tiempo de cálculo en un 70%. 空间相互作用模型通常采用离散区域代表区位。模型的计算量往往与区域数量呈平方甚至更高阶增长。对于可计算的精细模型,如土地利用‐交通相互作用模型和基于行为的城市区域模型,区域尺度的依赖性是长期存在的问题,即使计算机的计算速度增加,该问题仍无法消除。因此,建模者需在模型空间分辨率和覆盖范围以及模型分析的严谨性和深度上做出权衡。本文介绍了一种新型的离散分区系统,目的在于减少空间相互作用模型估算和计算时间,同时维持其精度。新系统的前提是目标区域的适当尺度取决于与初始区域的距离：在短距离范围内,空间精确性是重要的,且目标区域必须是小的;在更远距离上,位置精度的重要性降低,目标区域可以变大。该方法为每个初始区域制定了具体的尺度地图。每个初始区域成为其自身地图的中心,被近邻的小区域和更远距离的大区域所包围。本文给出了新方法的理论公式,并以英格兰地区的通勤模型进行检验。结果显示,尽管区域对的数量减少了96%,计算时间缩短了70%,但新方法的计算结果等效于常规模型。