This Perceptual Dialectology study of three dialects spoken in the South of Noord-Brabant in the Netherlands (Roosendaals, Oudenbosch, and Ruchpens) explored to what degree people from these towns...Show moreThis Perceptual Dialectology study of three dialects spoken in the South of Noord-Brabant in the Netherlands (Roosendaals, Oudenbosch, and Ruchpens) explored to what degree people from these towns are aware of the dialect features that make up their dialect, what these dialect features are and if these people are aware of the differences and similarities between their own dialect and that of the other two towns. The participants were thirty dialect speakers who are born, raised and still residential in one of the three studied towns. Interviews were held with these participants in which they were asked about their views on and knowledge about their own dialect and that of the two other towns. From these interviews it has become clear that, although Roosendaals, Oudenbosch and Rucphens have similarities, they do differ from each other on a lexical and a phonetic level. Most importantly, the results suggest that one’s level of sociophonetic awareness of their dialect relates to what degree they are capable of speaking Standard Dutch.Show less
This research examines fracture risks in post-Medieval the Netherlands. The challenges of daily life as well as interpersonal violence means humans are always at risk of fractures to the skeleton....Show moreThis research examines fracture risks in post-Medieval the Netherlands. The challenges of daily life as well as interpersonal violence means humans are always at risk of fractures to the skeleton. Given the occurrence of fractures across societies archaeologists have the opportunity to compare the fracture risk between populations and investigate the effects of social and economic standing. Research into long bone fractures in the Netherlands has been done for medieval sites, but not for post medieval sites. This research addresses this gap in fracture research. The main question of this research is: What can the analysis of long bone fractures tell us about life in various places in post-medieval the Netherlands. The first sub question tests the hypothesis that the position, and pattern of fractures was influenced by the socioeconomic status and lifestyle of the inhabitants of Middenbeemster. The second and third sub questions compare the frequency and distribution of long bone fractures (clavicle, humerus, radius, ulna, femur, tibia, and fibula) from four post-medieval the Netherlands sites (Eindhoven, Gouda, Middenbeemster and Roosendaal) from different socioeconomic backgrounds (e.g. low and high status) and living environments (e.g. urban and rural). The data from the Middenbeemster sample was collected by the author the other data was drawn from reports and books. There were three main findings in this research. First, it found that the assemblage from Middenbeemster has fractures that are consistent with traditional farming injuries, but differed from those described in other bioarchaeological studies, suggesting that farming in post-medieval the Netherlands might have been different or posted different dangers from those in other places. Second it found that the urban site of Eindhoven had significantly more long bone fractures compared to the rural site of Middenbeemster. There was also a difference in the distribution of fractures between the sites. This suggests that in post-medieval the Netherlands urban living had more risks of long bone fractures than rural living. Third, there was no difference in the long bone fracture rate between the high status site of Gouda and the low status site of Roosendaal. This shows that socioeconomic status did not have a significant effect on fracture risk. This thesis has broadened our understanding of fracture risk in post-medieval the Netherlands by providing some preliminary conclusions about the relationship between environmental and socioeconomic factors and fracture risk. This research, however, still requires more comparative data sets to confirm these preliminary conclusions, and test new hypotheses.Show less
