Melville and Nietzsche: Living the Death of God

Herman Melville was so estranged from the religious beliefs of his time and place that his faith was doubted during his own lifetime. In the middle of the twentieth century some scholars even associated him with nihilism. To date, however, no one has offered a detailed account of Melville in relation to Nietzsche, who first made nihilism a topic of serious concern to the Western philosophical tradition. In this essay, I discuss some of the hitherto unexplored similarities between Melville’s ideas and Nietzsche’s reflections on and reactions to the death of God and the advent of nihilism in the West

The impact of local ICT initiatives on social capital and quality of life

This paper reviews the evidence for the effects of local ICT initiatives (‘community networks’) on neighbourhood social capital and quality of life and has been developed from the public SOCQUIT D11 report (Anderson et al, 2006)

The Child Adoption Marketplace: Parental Preferences and Adoption Outcomes

In the United States child adoption costs vary considerably, ranging from no out-of-pocket expense to $50,000 or more. What are the causes for the variability in adoption expenses? We administered a survey to a sample of Michigan adoptive families to link adoptive parent characteristics, child characteristics, and adoption-related expenses and subsidies. We then estimate “hedonic” regressions in which adoption cost is a function of child characteristics. The analysis shows that most of the variation in adoption costs is explained by child characteristics. In particular, costs lower for older children, children of African descent, and special needs children. Findings inform policies regarding the transition of children from foster care to adoptive families.child welfare, adoption, subsidy

Guided Open Vocabulary Image Captioning with Constrained Beam Search

Existing image captioning models do not generalize well to out-of-domain images containing novel scenes or objects. This limitation severely hinders the use of these models in real world applications dealing with images in the wild. We address this problem using a flexible approach that enables existing deep captioning architectures to take advantage of image taggers at test time, without re-training. Our method uses constrained beam search to force the inclusion of selected tag words in the output, and fixed, pretrained word embeddings to facilitate vocabulary expansion to previously unseen tag words. Using this approach we achieve state of the art results for out-of-domain captioning on MSCOCO (and improved results for in-domain captioning). Perhaps surprisingly, our results significantly outperform approaches that incorporate the same tag predictions into the learning algorithm. We also show that we can significantly improve the quality of generated ImageNet captions by leveraging ground-truth labels.Comment: EMNLP 201