Improving the use of history by the international humanitarian sector

Abstract

This article challenges the often implicit assumption by historians working on humanitarian history that their work is being read and used by present-day humanitarian workers. Key characteristics of the modern-day humanitarian sector are highlighted, including the unpredictable and often inadequate levels of funding, stressful working conditions and high staff turnover. The article argues that, to a significant degree, the humanitarian sector is ahistorical and locked into a state of ‘perpetual present’. Two principal obstacles to the greater use of historical knowledge within the present-day humanitarian sector are identified as being the limited accessibility of the available literature on humanitarian history and the perceptions that the work of humanitarian historians is of limited relevance. The paper concludes by describing recent initiatives including the planned humanitarianhistory.org website which is intended to improve the accessibility of the available literature and facilitate engagement and co-production between historians and humanitarian workers.     

A Combined Cluster and Interaction Model: The Hierarchical Assignment Problem

This article presents a new spatial modeling approach that deals with interactions between individual geographic entities. The developed model represents a generalization of the transportation problem and the classical assignment problem and is termed the hierarchical assignment problem (HAP). The HAP optimizes the spatial flow pattern between individual origin and destination locations, given that some grouping, or aggregation of individual origins and destinations is permitted to occur. The level of aggregation is user specified, and the aggregation step is endogenous to the model itself. This allows for the direct accounting of aggregation costs in pursuit of optimal problem solutions. The HAP is formulated and solved with several sample data sets using commercial optimization software. Trials illustrate how HAP solutions respond to changes in levels of aggregation, as well as reveal the diverse network designs and allocation schemes obtainable with the HAP. Connections between the HAP and the literature on the p-median problem, cluster analysis, and hub-and-spoke networks are discussed and suggestions for future research are made.     

Bedding, hearths, and site maintenance in the Middle Stone Age of Sibudu Cave, KwaZulu-Natal, South Africa

Micromorphological analysis of sediments from the Middle Stone Age site of Sibudu Cave, KwaZulu-Natal, South Africa, provides a high-resolution sequence and evidence of site formation processes of predominantly anthropogenic deposits. This methodology allows for a detailed interpretation of individual anthropogenic activities, including the construction of hearths and bedding and the maintenance of occupational surfaces through the sweep out of hearths and the repeated burning of bedding. This analysis also provides a context for evaluating other studies at the site relating to magnetic susceptibility, paleobotany, paleozoology, anthracology, and studies of ochre.     

Geostatistical Smoothing of Areal Data: Mapping Employment Density with Factorial Kriging

This article summarizes area-to-point (ATP) factorial kriging that allows the smoothing of aggregate, areal data into a continuous spatial surface. Unlike some other smoothing methods, ATP factorial kriging does not suppose that all of the data within an area are located at a centroid or other arbitrary point. Also, unlike some other smoothing methods, factorial kriging allows the user to utilize an autocovariance function to control the smoothness of the output. This is beneficial because the covariance function is a physically meaningful statement of spatial relationship, which is not the case when other spatial kernel functions are used for smoothing. Given a known covariance function, factorial kriging gives the smooth surface that is best in terms of minimizing the expected mean squared prediction error. I present an application of the factorial kriging methodology for visualizing the structure of employment density in the Denver metropolitan area.     

Pressurised pastoralism in South Gobi, Mongolia: what is the role of drought?

The desert-steppe region of southern Mongolia is susceptible to drought and extreme winter weather ( dzud ) that in combination form Mongolia's worst natural hazard. Low precipitation and high climatic variability in this dryland environment impact the landscape and affect pastoralism, the dominant rural lifestyle. Using the Standardised Precipitation Index (SPI), this paper identifies drought occurrence in South Gobi Province, Mongolia. It then examines the relationship of drought with climate factors, interaction with vegetation (derived from Normalised Difference Vegetation Index - NDVI - data), and local human and livestock populations, and the dzuds of 1999–2001. Results show that drought is recurrent in the region, reaching extreme intensity most recently in 2005–2006. In contrast with the prevailing concept of drought impacting dzuds , the study did not find a connection between drought and dzud in South Gobi Province. Though repeated events, these natural hazards occur independently in the region. Climatic variables show increasing temperatures (>1°C), fluctuating precipitation patterns and a decline in vegetation cover. The principal long-term correlation of drought is with human population rather than natural factors, dzud or livestock numbers.