Everyday legitimacy and international administration: global governance and local legitimacy in Kosovo

International administrations are a very specific form of statebuilding. This paper examines the limits illustrated by the experience in Kosovo. Here, the international administration faced the same requirements of any legitimate, Liberal government, but without the checks and balances normally associated with Liberal governance. Thus, the international administration was granted full authority and the power thereby associated, but without the legitimacy upon which the Liberal social contract rests. The state-building agenda put forth came to be seen as more exogenous, reinforcing the delegitimization process. This paper will specifically address the influence of the Weberian approach to legitimacy on the statebuilding literature, as well as its limits. It will then propose other possible avenues for statebuilding, more in line with a wider understanding of legitimacy and intervention

Systematic Grant and Funding Body Acknowledgment Data for Publications: An Examination of New Dimensions and New Controversies for Bibliometrics

Bibliographic databases are beginning to provide systematic grant and funding body acknowledgement data for the publications they index. This paper considers how this new data might be used for policy purposes and the key issues that are likely to arise in its use. While the attempt to provide this kind of systematic data is in its relative infancy, there is already sufficient information within the WOS database to examine a number of controversies in science studies. This paper considers one such issue, namely the relationship between the number of funding sources acknowledged and the citation impact of publications where a positive relationship has been assumed to exist. Analyses of sets of publications from 2009 from the journals Cell and Physical Review Letters give contrasting results, suggesting that our understanding of the issue of the relationship between the impact of a publication and the number of funding sources which it acknowledges is not fully understood and may be more complicated that previously considered. It is proposed that scientific research findings are packaged by researchers into papers in a variety of ways for a wide variety of purposes. Individual funding quanta from whatever source are not therefore inputs to papers directly; rather, such funding supports a process that has amongst its outcomes, the production of papers

Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with (“lesional”) and without (“non-lesional”) radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68–75%) compared to models to lateralize the side of TLE (56–73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67–75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68–76%) than models that stratified non-lesional patients (53–62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care

Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study

Neurodevelopment continues through adolescence, with notable maturation of white matter tracts comprising regional fiber systems progressing at different rates. To identify factors that could contribute to regional differences in white matter microstructure development, large samples of youth spanning adolescence to young adulthood are essential to parse these factors. Recruitment of adequate samples generally relies on multi-site consortia but comes with the challenge of merging data acquired on different platforms. In the current study, diffusion tensor imaging (DTI) data were acquired on GE and Siemens systems through the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a multi-site study designed to track the trajectories of regional brain development during a time of high risk for initiating alcohol consumption. This cross-sectional analysis reports baseline Tract-Based Spatial Statistic (TBSS) of regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1), and radial diffusivity (LT) from the five consortium sites on 671 adolescents who met no/low alcohol or drug consumption criteria and 132 adolescents with a history of exceeding consumption criteria. Harmonization of DTI metrics across manufacturers entailed the use of human-phantom data, acquired multiple times on each of three non-NCANDA participants at each site’s MR system, to determine a manufacturer-specific correction factor. Application of the correction factor derived from human phantom data measured on MR systems from different manufacturers reduced the standard deviation of the DTI metrics for FA by almost a half, enabling harmonization of data that would have otherwise carried systematic error. Permutation testing supported the hypothesis of higher FA and lower diffusivity measures in older adolescents and indicated that, overall, the FA, MD, and L1 of the boys was higher than that of the girls, suggesting continued microstructural development notable in the boys. The contribution of demographic and clinical differences to DTI metrics was assessed with General Additive Models (GAM) testing for age, sex, and ethnicity differences in regional skeleton mean values. The results supported the primary study hypothesis that FA skeleton mean values in the no/low-drinking group were highest at different ages. When differences in intracranial volume were covaried, FA skeleton mean reached a maximum at younger ages in girls than boys and varied in magnitude with ethnicity. Our results, however, did not support the hypothesis that youth who exceeded exposure criteria would have lower FA or higher diffusivity measures than the no/low-drinking group; detecting the effects of excessive alcohol consumption during adolescence on DTI metrics may require longitudinal study