Chad Wellmon

Kant and the Feelings of Reason

This essay brings Kants notion of a philosophical medicine or a practical dietetics to bear on his ethics and, more precisely, the place of feeling within it. It argues that Kant offers up a dietetic regime in his Kritik der praktischen Vernunft designed to prevent a pathological subjectivity or, what he terms, solipsism by cultivating moral feelings. But this ethical discipline involves not so much the extirpation of feelings or affect than the modification of their place in the larger human economy. Kants moral regimens cultivate particular feelings as necessary and indispensable elements of moral being. For Kant, reason not only legislates: it needs, it feels, it suffers, and disciplines, and a disciplined reason is an embodied reason, a reason bound to particular human beings and particular practices.

Feature Learning for Footnote-Based Document Image Classification.

Classifying document images is a challenging problem that is confronted by many obstacles; specifically, the pivotal need of hand-designed features and the scarcity of labeled data. In this paper, a new approach for classifying document images, based on the availability of footnotes in them, is presented. Our proposed approach depends mainly on a Deep Belief Network (DBN) that consists of two phases, unsupervised pre-training and supervised fine-tuning. The main advantage of using this approach is its capability to automatically engineer the best features to be extracted from a raw document image for the sake of generating an efficient representation of it. This feature learning approach takes advantage of the vast amount of available unlabeled data and employs it with the limited number of labeled data. The obtained results show that the proposed approach provides an effective document image classification framework with a highly reliable performance.

Footnote-Based Document Image Classification

Analyzing historical document images is considered a challenging task due to the complex and unusual structures of these images. It is even more challenging to automatically find the footnotes in them. In fact, detecting footnotes is one of the essential elements for scholars to analyze and answer key questions in the historical documents. In this work, we present a new framework for footnote detection in historical documents. To this aim, we used the most salient feature of the footnotes, which is their smaller font size compared to the rest of the page content. We proposed three types of features to track the font size changes and fed them to two classifiers: SVM and AdaBoost. The framework shows promising results over 80% for both classifiers using our dataset.

LOYAL WORKERS AND DISTINGUISHED SCHOLARS: BIG HUMANITIES AND THE ETHICS OF KNOWLEDGE

Over the past two decades, long-running debates about the purposes and practices of humanistic inquiry have been refocused as a debate about the uncertain fate of the humanities in a digital age. Now, with the advent of digital and computational humanities, scholars are discussing with a new urgency what the humanities are for and what it means to practice them. And many suggest that the surfeit of digital data is unprecedented and are calling for new methods, practices, and epistemologies. This article considers these claims in light of a longer history of what Lorraine Daston has called “practices of compendia”––practices of collecting, collating, and interpreting massive amounts of data. It focuses, in particular, on the late nineteenth-century German historian Theodor Mommsen and the range of projects he initiated and led as secretary of the Prussian Academy of Sciences. Mommsen invented the “big humanities” and what his contemporaries termed the “industrial” model of scholarship, a model that helped create a new, modern scholarly persona and a distinctly modern ethics of knowledge.