Paleo-parasitological study on the soils collected from archaeological sites in old district of Seoul City

A paleo-parasitological study was performed on soil samples from archaeological sites in the old district of Seoul Metropolitan City (Old Seoul City) where the capital of the Joseon Kingdom was constructed about 600 years ago. The sampling sites were the original locations of the Royal Palace Wall, Yukjo Street and the Royal Arsenal. Microscopic examinations showed that parasite eggs of Clonorchis sinensis, Diphyllobothrium latum, Ascaris sp. and Trichuris sp. remained in the soil strata, which were estimated to represent the 14th-19th centuries. We suspect that the medieval citizens of Old Seoul City, numbering around 200,000, might have been made vulnerable to parasite infection by a combination of bad hygiene, inadequate sewer system and seasonal flooding.     

Three Common Machine Learning Algorithms Neither Enhance Prediction Accuracy Nor Reduce Spatial Autocorrelation in Residuals: An Analysis of Twenty-five Socioeconomic Data Sets

Machine learning (ML) is being applied in an increasing volume of geographical research. However, the aspects of spatial autocorrelation (SAC) in the residuals produced by ML models have been understudied compared to the benefit of ML, namely, reduction of prediction errors. In this study, we examined the relationship between predictive accuracy and the reduction in the residual SAC for 597 variables from 25 geographical socio-economic data sets using spatial and nonspatial cross-validation of three ML algorithms such as random forests, support vector machine, and artificial neural network (ANN) to provide an extensive empirical diagnosis—but not a definitive theory—of the relationship between SAC and ML. Our results highlighted that the ML algorithms with tuned hyperparameters yielded marginal predictive accuracy gains and the minimal decreases in residual SAC. ANN revealed lower accuracy and higher reduction in the residual SAC than others. This implies ML algorithms in geographical research in socio-economic domains would not always result in higher prediction accuracy. We suggest that ML in geographical research should be cautiously employed when the main objective is related to the residual SAC. We also showed that spatial cross-validation neither improves predictive accuracy substantially nor reduce the residual SAC effectively.     

The Majority Theorem for the Single (p = 1) Median Problem and Local Spatial Autocorrelation

Except for about a half dozen papers, virtually all (co)authored by Griffith, the existing literature lacks much content about the interface between spatial optimization, a popular form of geographic analysis, and spatial autocorrelation, a fundamental property of georeferenced data. The popular p-median location-allocation problem highlights this situation: the empirical geographic distribution of demand virtually always exhibits positive spatial autocorrelation. This property of geospatial data offers additional overlooked information for solving such spatial optimization problems when it actually relates to their solutions. With a proof-of-concept outlook, this paper articulates connections between the well-known Majority Theorem of the 1-median minisum problem and local indices of spatial autocorrelation; the LISA statistics appear to be the more useful of these later statistics because they better embrace negative spatial autocorrelation. The relationship articulation outlined here results in the positing of a new proposition labeled the egalitarian theorem.     

Does It Pay for US‐based NGOs to Go to War? Empirical Evidence for Afghanistan and Iraq

Apart from altruistic reasons, NGOs may engage in developing countries under conditions of conflict and war in order to secure funding and survive in the ‘market’ of humanitarian relief and development assistance. Applying difference‐in‐differences approaches, this article analyses empirically whether the presence of US‐based NGOs in Afghanistan and Iraq improved their chances of external funding. While there are some indications that NGOs active in Afghanistan had better access to official funding, the authors do not find statistically compelling evidence that it pays for NGOs to engage where the United States intervenes militarily.     

Hydraulically fractured: Unconventional gas and anthropology (Respond to this article at http://www.therai.org.uk/at/debate)

The predicted increase in unconventional gas production is set to change global energy and concomitant geopolitical relations. The scale and required infrastructure of unconventional gas extraction result in profound changes in the landscape where extraction and processing take place. Widespread public concerns about the impacts of this industry have emerged, particularly with regard to fracking, surface and subterranean water contamination, air pollution and a host of other environmental issues, as well as social impacts and health risks. This article sets out some of the emerging anthropological engagements with unconventional gas and fracking, including analyses of materiality, politics, discourses, rights, risk and knowledge.