• Digital Humanities and Cultural Heritage
• 2012-2021close
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What does an anthropologist’s archive look like? Where is it located? And is the anthropology of archives important for the understanding of anthropological thinking today? Here we answer these questions by analysing the various life histories of the archival fragments of one of the most puzzling and influential anthropologists in the history of Russian and Soviet anthropology: Sergei Mikhailovich Shirokogoroff (1887–1939). Shirokogoroff is credited as being one of the authors of the etnos theory — one of the main instruments of identity politics in Russia, China, Germany and also, in part, Japan and South Africa. The transnational life histories of Shirokogoroff and his wife Elizaveta [Elizabeth] Nikolaevna (1884–1943), and of their ideas, suggests a conception of the archive not as a single whole, but instead as a collection of forgotten, hidden, obliterated, or, on the other hand, scrupulously preserved fragments. These fragments are not centred in one place or organized around any one reading, but they nevertheless represent “partial connections”. Moreover, as we can see today with hindsight, none of these archival fragments lay inert. They have been intertwined in local political and social ontologies. Our text has an autoethnograpic quality. While illustrating separate episodes from the life of the Shirokogoroffs we also will tell of our search for the manuscripts through which we were forced onto strange paths and encounters. These greatly deepened our understanding both of the life of documents and their material links to the lives of researchers. Our article is an attempt to illustrate this complex picture which, in the end, will allow us to conclude that we have only just begun to understand the workings of the anthropologist’s archive in the history of anthropological thought. QC 20220530

Can walking trails be understood not only as routes to history and heritage, but also as heritage in and of themselves? The paper explores the articulation of trails as a distinct landscape and mobility heritage, bridging the nature-culture divide and building on physical and intellectual movements over time. The authors aim to contribute to a better understanding of the geography of trails and trailscapes by analysing the emergence of the Swedish-Norwegian trail Finnskogleden. The trail is situated in the border region spanning the former county of Hedmark in present-day Innlandet County, south-eastern Norway, and Värmland County in mid-western Sweden, a forested area where Finnish-speaking immigrants settled from the 16th century to the early 20th century. Archives, literature, interviews, and field visits were used to analyse the emergence and governance of the trail. The main finding is the importance of continuous articulation work by local and regional stakeholders, through texts, maps, maintenance, and mobility. In conclusion, the Finn forest trailscape and its mobility heritage can be seen as an articulation of territory over time, a multilayered process drawing on various environing technologies, making the trail a transformative part of a trans-border political geography.  QC 20220308

We present an online API to access a number of Natural Language Processing services developed at KTH. The services work on Swedish text. They include tokenization, part-of-speech tagging, shallow parsing, compound word analysis, word inflection, lemmatization, spelling error detection and correction, grammar checking, and more. The services can be accessed in several ways, including a RESTful interface, direct socket communication, and premade Web forms. The services are open to anyone. The source code is also freely available making it possible to set up another server or run the tools locally. We have also evaluated the performance of several of the services and compared them to other available systems. Both the precision and the recall for the Granska grammar checker are higher than for both Microsoft Word and Google Docs. The evaluation also shows that the recall is greatly improved when combining all the grammar checking services in the API, compared to any one method, and combining services is made easy by the API. QC 20230328

Cet article traite des tensions socio-politiques dans la Hongrie de la fin des Habsbourg en explorant des pratiques répressives de la gendarmerie royale hongroise de sa création en 1881 jusqu’à la Première Guerre mondiale. Une analyse qualitative et statistique de sources primaires montre comment la gendarmerie a protégé la double monarchie contre les menaces perçues des mouvements nationalistes et ouvriers. Cet article cherche à identifier les situations où les gendarmes ont eu recours aux violences physiques, les régions où les violences étaient les plus fortes et comment elles ont évolué au cours du temps. Il défend que le recours aux violences physiques, notamment sous l’action des gendarmes royaux, est une caractéristique clé des conflits socio-politiques dans la Hongrie de la Belle Époque. This article deals with the social-political tensions in late Habsburg Hungary by exploring the coercive conduct of the Hungarian Royal Gendarmerie from its creation in 1881 up to the First World War. Through an analysis of narrative and statistical primary sources, the paper shows how the gendarmerie protected the dualist system from the perceived threats of nationalist and labour movements. It attempts to establish the situations in which the gendarmes resorted to physical aggression, how its dynamic changed over time, and the regions where the levels of force exercised by the gendarmerie were higher. Altogether, it argues that widespread physical violence was a central feature of social-political conflicts in pre-WW1 Hungary, with the gendarmes playing a crucial role.  QC 20230731 Prewaras

Advanced NLP models require huge amounts of data from various domains to produce high-quality representations. It is useful then for a few large public and private organizations to join their corpora during training. However, factors such as legislation and user emphasis on data privacy may prevent centralized orchestration and data sharing among these organizations. Therefore, for this specific scenario, we investigate how gossip learning, a massively-parallel, data-private, decentralized protocol, compares to a shared-dataset solution. We find that the application of Word2Vec in a gossip learning framework is viable. Without any tuning, the results are comparable to a traditional centralized setting, with a reduction in ground-truth similarity scores as low as 4.3%. Furthermore, the results are up to 54.8% better than independent local training. QC 20210423

The patterns of syntactic differentiation and their causes and effects are fundamental to space syntax analysis. Often, however, differentiation is taken for granted with no reference to the dynamic process that brings it about. Here, we first show that by measuring the amount of syntactic differentiation, we can better distinguish between types of street networks. We then show that repeated local transformations of a regular street grid lead to different yet largely predictable trajectories of differentiation depending upon the rules used. Finally, we show that different paths to differentiation entail different costs in terms of undesirable properties. This allows us to better assess the likely consequences of design moves and their appropriateness relative to design intentions. QC 20210614

The automatic interpretation of sign languages is a challenging task, as it requires the usage of high-level vision and high-level motion processing systems for providing accurate image perception. In this paper, we use Convolutional Neural Networks (CNNs) and transfer learning to make computers able to interpret signs of the Swedish Sign Language (SSL) hand alphabet. Our model consists of the implementation of a pre-trained InceptionV3 network, and the usage of the mini-batch gradient descent optimization algorithm. We rely on transfer learning during the pre-training of the model and its data. The final accuracy of the model, based on 8 study subjects and 9400 images, is 85%. Our results indicate that the usage of CNNs is a promising approach to interpret sign languages, and transfer learning can be used to achieve high testing accuracy despite using a small training dataset. Furthermore, we describe the implementation details of our model to interpret signs as a user-friendly web application. QC 20220905