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Modern Haredim (ultra-Orthodox Israelis who have joined the army, workforce, and academia) are often perceived as a sign that contemporary Haredi society is becoming more liberal and Western. This article presents an alternative framework, which understands the challenge posed by modern Haredim to the classic Haredi society of learners not in terms of increasing liberalism but rather of increasing radicalism. What is peculiar to modern Haredim is not a greater openness toward secular society, but rather a profound change in the theory and practice of religious activity. Modern Haredim perceive the entire world as a potential arena for religious activity and reject the confinement of religious life to the boundaries of the house of study. Studying various radical activities of modern Haredim—which resonate with much earlier trends within Jewish Orthodoxy—this article argues that the religious attitudes developing in contemporary Haredi society are inner-worldly in orientation.

Book review of conference papers of international conference 'A million pictures', August 29-September 1, 2017, at Utrecht University

AbstractIn April 1848, a proclamation of friendship to the Germans sent by the Provisional Government of Milan to the Fünfzigerausschuss (Committee of Fifty) in Frankfurt was rejected by the latter, creating widespread outrage in Italy. Concurrently, a parallel controversy over the possession of South Tyrol arose between the two revolutions. This article provides an exploratory analysis of these two episodes, examining the role they played in shaping relations between the two revolutions, and in influencing the image Italians had of the revolution in Germany. Shedding light on an episode until now overlooked by historiography, this article seeks to contribute to the salient debate on the peculiar relationship between internationalist ideals and nationalist claims during the 1848 revolution. It argues that the disillusioning impact on revolutionary audiences of specific ‘episodes of friction’, such as those examined in this article,was greater than the ‘natural convergence of goals’ of the various national revolutions in 1848.

This book is the first extensive research on the role of poetry during the Iranian Revolution (1979) and the Iran-Iraq War (1980-1988). How can poetry, especially peaceful medieval Sufi poems, be applied to exalt violence, to present death as martyrdom, and to process war traumas? Examining poetry by both Islamic revolutionary and established dissident poets, it demonstrates how poetry spurs people to action, even leading them to sacrifice their lives. The book's originality lies in fresh analyses of how themes such as martyrdom and violence, and mystical themes such as love and wine, are integrated in a vehemently political context, while showing how Shiite ritual such as the pilgrimage to Mecca clash with Saudi Wahhabi appreciations. A distinguishing quality of the book is its examination of how martyrdom was instilled in the minds of Iranians through poetry, employing Sufi themes, motifs and doctrines to justify death. Such inculcation proved effective in mobilising people to the front, ready to sacrifice their lives. As such, the book is a must for readers interested in Iranian culture and history, in Sufi poetry, in martyrdom and war poetry. Those involved with Middle Eastern Studies, Iranian Studies, Literary Studies, Political Philosophy and Religious Studies will benefit from this book.

Jewish funerary culture, despite vast amounts of available data, has yet to benefit from comprehensive analyses. While a great amount of data is digitized and available online, it is nonetheless dispersed on various websites, whose databases are unrelated and incompatible with one another. Other data exists only in printed form, and is even less available. My paper will present a new project that intends to modify this state of affairs: PEACE, standing for Portal of Epigraphy, Archaeology, Conservation and Education on Jewish Funerary Culture.

The Dutch police force generates very high amounts of documents such as transcripts of interrogations, evidence findings, statements of people involved, all of which need to be read and processed by analysts. Automating the entity extraction in the documents would greatly help the police force. Neural network-based approaches using contextual word embeddings are considered the current state-of-the-art approach to tackle the named entity recognition (NER) problem in the Dutch. There are available domain-independent NER datasets in the literature well as pre-trained NER models. However, earlier studies show that domain-independent models do not work well for domain-specific tasks. As annotation is highly costly, in this study, we train a set of BERTje embeddings based NER models with the varying size of police dataset in addition to the domain-independent set to observe the effect of domain-specific dataset in the training. We follow a training, validation, and test split to ensure a proper experimental protocol. We observe that the slope of the performance increase is decreasing with the number of target domain documents in the training set and stabilizes on the validation set around 250-300 documents. The NER system has a better performance on the held-out test set (85\% macro-average F1 score over five entity categories) compared to the validation set, showing the generalization power of the investigated framework.

In the domain of the Dutch cultural heritage various data sets describe different aspects of life during the Dutch Golden Age.These data sets, in the form of RDF graphs, use different standards and contain noise in the values of literal nodes, such as misspelled names and uncertainty in dates. The Golden Agents project aims at answering queries about the Dutch Golden ages using these distributed and independently maintained data sets. A problem in this project, among many other problems, is the identification of persons who occur in multiple data sets but under different URI’s. This paper aims to solve this specific problem and generate a linkset, i.e. a set of pairs of URI’s which are judged to represent the same person. We use domain knowledge in the application of an existing node context generation algorithm to serve as input for GloVe, an algorithm originally designed for embedding words. This embedding is then used to train a classifier on pairs of URI’s which are known duplicates and non-duplicates. Using just the cosine similarity between URI-pairs in embedding space for prediction,we obtain a simple classifier with an F12-score of around 0.85, even when very few training examples are provided. On larger training sets, more complex classifiers are shown to reach an F12-score ofup to 0.88