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This article brings to bear findings from the debate on the boundary problem in democratic theory on discussions of workplace democracy to argue that workplace democrats’ focus on workers is unjustified and that more constituencies will have to be included in any prospective scheme of workplace democracy. It thereby provides a valuable and underdiscussed perspective on workplace democracy that goes beyond the debate’s usual focus on the clarification and justification of workplace democrats’ core claim. It also goes beyond approaches like stakeholder theory in law and economics that determine decision-making rights without taking into account genuinely democratic considerations. My discussion proceeds by considering three principles for inclusion from democratic theory for the specific case of the corporation. I submit that two of them, the all-coerced and the all-subjected principle, are not appropriate for this specific case, because they cannot capture the distinguishing features of the corporation. The all-affected principle however is appropriate but has a very wide range. I further argue that this is not as big of a problem as it first might seem and that this principle is still the most appropriate for defining the demos of the democratic corporation. The article closes by pointing out the consequences of this result for the workplace democracy debate and for the legitimacy of the market as a coordination mechanism.

This is collection of all the stories' titles published on Wattpad at the date: January 2018. It's a corpus of around 30 millions titles in more than 50 different languages. It includes mainly original fiction and a small part of fan fiction (roughly 10%). The R Markdown files regarding the procedures for network analysis and sentiment analysis can be found in the GitHub repository: https://github.com/SimoneRebora/Wattpad_analysis We published an article based on this data https://doi.org/10.1371/journal.pone.0226708

In the last few decades, migrants’ past experiences and memories have become increasingly recognized as a heritage. While this can be seen as a positive shift towards a more inclusive evaluation of the past, migration heritage is still overwhelmingly portrayed through a binary between the country of origin and country of settlement. This tendency obscures the multiple transnational connections migrants sustain with different locations along the migration process. Drawing on examples of Chinese migration to Europe, this article argues in favour of forgoing the national(istic) approach to heritagization and instead focusing on the connections formed during a century of Chinese migration to Europe.

Background: Historical ethnobotanical data can provide valuable information about past human-nature relationships as well as serve as a basis for diachronic analysis. This data note aims to present a dataset which documented medicinal plant uses, mentioned in a selection of German-language sources from the 19th century covering the historical regions of Estonia, Livonia, Courland, and Galicia. Methods: Data was mainly obtained by systematic manual search in various relevant historical German-language works focused on the medicinal use of plants. Data about plant and non-plant constituents, their usage, the mode of administration, used plant parts, and their German and local names was extracted and collected into a database in the form of Use Reports.

International audience; Published in OA on RESSI (http://www.ressi.ch/) at the end of Octobre 2021. We present here highlights from an enquiry on the innovations in scholarly writing in the Humanities and Social Sciences in the H2020 project OPERAS-P. This article explores the theme of Open Research Data and its role in the emergence of new models of scholarly writing. We examine more closely the obstacles and fostering conditions to the publication of research data, both from a social and a technical perspective.

Mexico’s so-called “War on Drugs” began as a war on poor people. This article locates the roots of Mexico’s current drug-related violence in a longer history of state terror and violence enacted against social movements and rural communities. The article traces this history by grounding it locally in the guerrerense municipality of Coyuca de Catalán. Resumen: El norte chiquito: De “guerras sucias” a guerras de drogas en Tierra Caliente de Guerrero La mal llamada “guerra contra las drogas” en México empezó como una guerra contra los pobres. Este articulo ubica las raíces de la violencia en el México contemporáneo dentro una historia de terrorismo de estado y violencia durante la década de los años 70. Para desenredar estas raíces, el artículo ofrece una perspectiva histórica y local basada en el municipio guerrerense de Coyuca de Catalán.

An increasing number of researchers support reproducibility by including pointers to and descriptions of datasets, software and methods in their publications. However, scientific articles may be ambiguous, incomplete and difficult to process by automated systems. In this paper we introduce RO-Crate, an open, community-driven, and lightweight approach to packaging research artefacts along with their metadata in a machine readable manner. RO-Crate is based on Schema$.$org annotations in JSON-LD, aiming to establish best practices to formally describe metadata in an accessible and practical way for their use in a wide variety of situations. An RO-Crate is a structured archive of all the items that contributed to a research outcome, including their identifiers, provenance, relations and annotations. As a general purpose packaging approach for data and their metadata, RO-Crate is used across multiple areas, including bioinformatics, digital humanities and regulatory sciences. By applying "just enough" Linked Data standards, RO-Crate simplifies the process of making research outputs FAIR while also enhancing research reproducibility. An RO-Crate for this article is available at https://www.researchobject.org/2021-packaging-research-artefacts-with-ro-crate/ Comment: 42 pages. Submitted to Data Science

Presentation given during the 2nd ESS-SUSTAIN-2 (#871063) consortium meeting (21/01/2021) for WP 6.

Recently, domain-general recurrent neural networks, without explicit linguistic inductive biases, have been shown to successfully reproduce a range of human language behaviours, such as accurately predicting number agreement between nouns and verbs. We show that such networks will also learn number agreement within unnatural sentence structures, i.e. structures that are not found within any natural languages and which humans struggle to process. These results suggest that the models are learning from their input in a manner that is substantially different from human language acquisition, and we undertake an analysis of how the learned knowledge is stored in the weights of the network. We find that while the model has an effective understanding of singular versus plural for individual sentences, there is a lack of a unified concept of number agreement connecting these processes across the full range of inputs. Moreover, the weights handling natural and unnatural structures overlap substantially, in a way that underlines the non-human-like nature of the knowledge learned by the network.