The geographical psychology of recent graduates in the Netherlands: Relating enviornmental factors and personality traits to location choice

There is ample evidence from different research disciplines that location factors such as employment opportunities or the availability of amenities and facilities are a powerful predictor of settlement behaviour. Recent research suggests that citizens’ mean personality traits could be an additional predictor of where young people settle. We therefore explore 1) the extent to which recent graduates in the Netherlands are geographically clustered with respect to five different personality traits, 2) whether the geographical clustering of graduates is intensified as they grow older, 3) how regional environmental characteristics are related to personality traits, and 4) the extent to which personality traits play a role in graduates’ location choices. Our results reveal a distinct geographical clustering of personality traits among the different regions in the Netherlands. We also show that this geographical clustering becomes more blurred as graduates age. The results furthermore show robust associations between personality traits and several environmental characteristics with respect to demographic, economic, health, political, sociocultural, crime, and religious outcomes. In addition, we show that personality traits play a role in graduates’ location choices. Economic factors seem to have a larger impact in determining location choices than personality traits

Sourcing the Sacred: Application of Reflectance Spectroscopy and Linear Morphometrics to Hopewell Mortuary Chert Discs

ABSTRACT: Despite being one of the most intensively-studied culture phenomena of precontact North America, Hopewell peoples and their communities remain largely enigmatic outside of ceremonial earthwork sites. This research aims to examine Ohio Hopewell community by proxy of the large cache of chert bifaces disinterred from Mound 2, located at the Hopewell Mound Group (33RO27) in Ross County, Ohio. Numbering approximately 8,600 bifaces, these artifacts exhibit broadly similar macroscopic traits, and have been attributed in past archaeological literature as coming from a single source in Indiana. This research hypothesizes that this attribution is erroneous, and that the interaction of geographically disparate Hopewell communities is visible here as a function of differential contributions of chert material that was locally available to them. Furthermore, it is hypothesized that if this locally-sourced chert was knapped into bifaces prior to deposition into Mound 2, that differences in gross form may represent individual communities practicing similar knapping techniques. These hypotheses are tested by subjecting a 172 member sample of the Mound 2 cache to VNIR/FTIR spectroscopy chert sourcing techniques coupled with linear morphometrics, agglomerative hierarchical clustering, and fuzzy k-means clustering. The results conclude that the 172 member sample group Mound 2 bifacial population is comprised of a variety of chert lithic materials that exhibit affinity to chert reference material obtained from multiple geographically distant chert sources within the Midwest and South. Their physical forms show broad differences in trends in biface manufacture between groups of artifacts sharing chert sources, suggesting multiple Hopewell communities gathering to participate in the construction of Mound 2

Optimization-based User Group Management : Discovery, Analysis, Recommendation

User data is becoming increasingly available in multiple domains ranging from phone usage traces to data on the social Web. User data is a special type of data that is described by user demographics (e.g., age, gender, occupation, etc.) and user activities (e.g., rating, voting, watching a movie, etc.) The analysis of user data is appealing to scientists who work on population studies, online marketing, recommendations, and large-scale data analytics. However, analysis tools for user data is still lacking.In this thesis, we believe there exists a unique opportunity to analyze user data in the form of user groups. This is in contrast with individual user analysis and also statistical analysis on the whole population. A group is defined as set of users whose members have either common demographics or common activities. Group-level analysis reduces the amount of sparsity and noise in data and leads to new insights. In this thesis, we propose a user group management framework consisting of following components: user group discovery, analysis and recommendation.The very first step in our framework is group discovery, i.e., given raw user data, obtain user groups by optimizing one or more quality dimensions. The second component (i.e., analysis) is necessary to tackle the problem of information overload: the output of a user group discovery step often contains millions of user groups. It is a tedious task for an analyst to skim over all produced groups. Thus we need analysis tools to provide valuable insights in this huge space of user groups. The final question in the framework is how to use the found groups. In this thesis, we investigate one of these applications, i.e., user group recommendation, by considering affinities between group members.All our contributions of the proposed framework are evaluated using an extensive set of experiments both for quality and performance.Les donn ́ees utilisateurs sont devenue de plus en plus disponibles dans plusieurs do- maines tels que les traces d'usage des smartphones et le Web social. Les donn ́ees util- isateurs, sont un type particulier de donn ́ees qui sont d ́ecrites par des informations socio-d ́emographiques (ex., ˆage, sexe, m ́etier, etc.) et leurs activit ́es (ex., donner un avis sur un restaurant, voter, critiquer un film, etc.). L'analyse des donn ́ees utilisa- teurs int ́eresse beaucoup les scientifiques qui travaillent sur les ́etudes de la population, le marketing en-ligne, les recommandations et l'analyse des donn ́ees `a grande ́echelle. Cependant, les outils d'analyse des donn ́ees utilisateurs sont encore tr`es limit ́es.Dans cette th`ese, nous exploitons cette opportunit ́e et proposons d'analyser les donn ́ees utilisateurs en formant des groupes d'utilisateurs. Cela diff`ere de l'analyse des util- isateurs individuels et aussi des analyses statistiques sur une population enti`ere. Un groupe utilisateur est d ́efini par un ensemble des utilisateurs dont les membres parta- gent des donn ́ees socio-d ́emographiques et ont des activit ́es en commun. L'analyse au niveau d'un groupe a pour objectif de mieux g ́erer les donn ́ees creuses et le bruit dans les donn ́ees. Dans cette th`ese, nous proposons un cadre de gestion de groupes d'utilisateurs qui contient les composantes suivantes: d ́ecouverte de groupes, analyse de groupes, et recommandation aux groupes.La premi`ere composante concerne la d ́ecouverte des groupes d'utilisateurs, c.- `a-d., compte tenu des donn ́ees utilisateurs brutes, obtenir les groupes d'utilisateurs en op- timisantuneouplusieursdimensionsdequalit ́e. Ledeuxi`emecomposant(c.-`a-d., l'analyse) est n ́ecessaire pour aborder le probl`eme de la surcharge de l'information: le r ́esultat d'une ́etape d ́ecouverte des groupes d'utilisateurs peut contenir des millions de groupes. C'est une tache fastidieuse pour un analyste `a ́ecumer tous les groupes trouv ́es. Nous proposons une approche interactive pour faciliter cette analyse. La question finale est comment utiliser les groupes trouv ́es. Dans cette th`ese, nous ́etudions une applica- tion particuli`ere qui est la recommandation aux groupes d'utilisateurs, en consid ́erant les affinit ́es entre les membres du groupe et son ́evolution dans le temps.Toutes nos contributions sont ́evalu ́ees au travers d'un grand nombre d'exp ́erimentations `a la fois pour tester la qualit ́e et la performance (le temps de r ́eponse)

CRAFT SPECIALIZATION AND THE EMERGENCE OF THE CHIEFLY CENTRAL PLACE COMMUNITY OF HE-4 (EL HATILLO), CENTRAL PANAMA

The development of chiefdoms has received considerable attention from archaeologists, but there remains little consensus with respect to the underlying causal mechanisms. In particular, the importance of an economic foundation to the emergence of chiefdoms has been the focus of some debate. Some scholars have argued that the mobilization of key resources such as land, labor, agricultural surplus or craft production is critical to the development of chiefdom polities as it implies a material foundation for political power. An alternative view places more importance on status competition and the display and exchange of prestige goods among emergent elites. Because it may be used to support either strategy, craft specialization has figured prominently in discussions of these two kinds of chiefly political economy. The focus of this dissertation is the degree to which specialized craft production was a significant factor in the development of chiefdoms at the central place community of He-4 in the Río Parita valley of Central Panama. The results of this dissertation show that craft specialization was relatively unimportant to the emergence of chiefdoms in the Río Parita valley during the Cubitá phase (A.D. 550-700), suggesting a social hierarchy based more on non-economic forms of social power, perhaps including feasting activities, warfare or involvement in local trade. The data from He-4 also show that the social hierarchy seen in the burial record after A.D. 700-900 develops in tandem with differences in household status that are apparent as early as the Cubitá phase (A.D. 550-700). These differences in household status become increasingly well developed over time; however, they are never as dramatic as the differences seen in the mortuary record for Central Panama. There is also no real connection between the emergence of the social hierarchy at He-4 and craft specialization. It is only during the Parita phase (A.D. 1100-1300) that craft specialization involving the final stages of axe manufacture and use of polished stone chisels becomes important activities in high status households at He-4