Citizenship as a legal concept: criteria for a debate in multicultural societies and democratic challenges

La propuesta de este trabajo parte del análisis de un fallo del Tribunal Electoral de México motivado por una impugnación extemporánea de miembros de una comunidad indígena a un acto jurídico. Dicha extemporaneidad se debió al acceso con demoras al periódThe aim of this paper is to analyze a sentence of Mexico s Federal Electoral Tribunal that harmonized the right of accessing to justice of the indigenous people with the rules that regulate it. In this sense, the key that delimitates citizenship is the c

The Legal Concept of Person and its Constitutional Hierarchy

La propuesta de este trabajo consiste en presentar una serie de argumentos que sustentan la siguiente afirmación: el concepto jurídico de persona posee una naturaleza formalmente legal y materialmente constitucional. En el hoy derogado Código Civil de la Nación Argentina, existía una definición del concepto jurídico de persona. En el actual Código Civil y Comercial, dicha definición no se encuentra explicitada aunque puede deducirse claramente de las referencias que aparecen en el articulado a las notas de inviolabilidad y dignidad que se le atribuyen. Por su aparición en dicho cuerpo normativo, la jerarquía del concepto es la que le corresponde a las leyes, es decir, el nivel de las normas jurídicas generales. No obstante, por el valor del contenido de dicho concepto y su relevancia dentro del ordenamiento jurídico, la naturaleza material del concepto jurídico de persona es de jerarquía constitucional.The aim of this paper is to present some arguments that support the thesis that the legal concept of person has a formally legal hierarchy but also a materially constitutional one. In the derogated civil code of Argentina, there was a definition of the legal concept of person. Nowadays, the new civil and commercial code has no definition of it but it does include some characteristics that every person has and that allow to deduce which kind of concept it provides. Because the concept appears in the civil code it has legal hierarchy. However, because of its substantive content and its relevance, it has constitutional hierarchy.Fil: Lell, Helga María. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa. Facultad de Ciencias Económicas y Jurídicas. Centro de Investigaciones en Ciencias Jurídicas; Argentin

Landowners or Lifeguards? \u3ci\u3eDegel v. Majestic Mobile Manor, Inc.\u3c/i\u3e and Liability for Visitors\u27 Injuries from Natural Bodies of Water

Under an exception to the attractive nuisance doctrine, landowners typically owe no duty to warn and protect trespassing children from the dangers inherent in ponds, streams, and other natural bodies of water located on the owners\u27 property. In Degel v. Majestic Mobile Manor, Inc., however, the Washington Supreme Court declined to extend this premises liability exception to situations where the injured visitor is an invitee of the landowner. This Note examines the natural bodies of water exception and argues that Degel\u27s refusal to apply it in the invitee context ultimately conflicts with the court\u27s earlier policy statement favoring access to the state\u27s waterways. The Note concludes by proposing an analytical framework that would ensure the continued recreational, visual, and environmental benefits derived from unfenced bodies of water located on business property, while simultaneously maintaining a duty of affirmative care upon landowners to protect invitees from water hazards only under carefully limited circumstances

The Split Matters: Flat Minima Methods for Improving the Performance of GNNs

When training a Neural Network, it is optimized using the available training data with the hope that it generalizes well to new or unseen testing data. At the same absolute value, a flat minimum in the loss landscape is presumed to generalize better than a sharp minimum. Methods for determining flat minima have been mostly researched for independent and identically distributed (i. i. d.) data such as images. Graphs are inherently non-i. i. d. since the vertices are edge-connected. We investigate flat minima methods and combinations of those methods for training graph neural networks (GNNs). We use GCN and GAT as well as extend Graph-MLP to work with more layers and larger graphs. We conduct experiments on small and large citation, co-purchase, and protein datasets with different train-test splits in both the transductive and inductive training procedure. Results show that flat minima methods can improve the performance of GNN models by over 2 points, if the train-test split is randomized. Following Shchur et al., randomized splits are essential for a fair evaluation of GNNs, as other (fixed) splits like 'Planetoid' are biased. Overall, we provide important insights for improving and fairly evaluating flat minima methods on GNNs. We recommend practitioners to always use weight averaging techniques, in particular EWA when using early stopping. While weight averaging techniques are only sometimes the best performing method, they are less sensitive to hyperparameters, need no additional training, and keep the original model unchanged. All source code is available in https://github.com/Foisunt/FMMs-in-GNNs

TRES CONCEPCIONES EN TORNO A LA CIENTIFICIDAD DEL DERECHO: NEGACIÓN POR SU VARIABILIDAD, ERRADICACIÓN SEMÁNTICA E INCORPORACIÓN DE LA INTERPRETACIÓN

En este artículo se sintetizan tres afamadas propuestas en torno a la cientificidad de la disciplina jurídica construidas a partir de lo que ocurre con el sentido de las normas jurídicas y de acuerdo a los criterios modernos de las ciencias. La primera de ellas, expuesta por von Kirchmann, constituye la más conocida concepción negatoria de la cientificidad basada en la constante variación de las instituciones jurídicas. La segunda y la tercera afirman la cientificidad disciplinar pero desde perspectivas diferentes. Kelsen construye su teoría acentuando las normas jurídicas en una versión formalizada al extremo, lo que implica desproveerlas de contenido y erradicar su sentido. Por su parte, Ehrlich sostiene la cientificidad pero reconoce el rol que ocupan los jueces en la interpretación normativa y los problemas que apareja el lenguaje

Gümnaasiumi praktilise valikkursuse „IoT lahendused“ väljatöötamine ja läbiviimine Tartu Jaan Poska Gümnaasiumi näitel

Magistritöö eesmärgiks oli välja töötada ja läbi viia praktiline valikkursus “IoT lahendused” gümnaasiumiastmele. Praktilise kursuse üheks eesmärgiks oli tutvustada õpilastele üht võimalust, kuidas tehnoloogia abil probleeme lahendada ja selle kaudu saada praktilisi kogemusi infotehnoloogia alal. Kursusel kasutati riistvaralise lahendusena ESP32 kiibil baseeruvat mikrokontrollerit ning digitaal- ja analoogandureid. IoT lahenduste loomiseks kasutati programmeerimiskeelt MicroPython. Materjali loomisel lähtuti ADDIE mudeli printsiipidest. Magistritöö autor piloteeris kursust Tartu Jaan Poska Gümnaasiumis 10.‒11. klasside õpilastega. Õpilaste tagasiside küsimustiku põhjal võib kursuse riistvara ja teemade valikuga rahule jääda. Kursuse läbiviimist jätkatakse Tartu Jaan Poska Gümnaasiumis järgnevatel õppeaastatel

Memorization of Named Entities in Fine-tuned BERT Models

Privacy preserving deep learning is an emerging field in machine learning that aims to mitigate the privacy risks in the use of deep neural networks. One such risk is training data extraction from language models that have been trained on datasets, which contain personal and privacy sensitive information. In our study, we investigate the extent of named entity memorization in fine-tuned BERT models. We use single-label text classification as representative downstream task and employ three different fine-tuning setups in our experiments, including one with Differentially Privacy (DP). We create a large number of text samples from the fine-tuned BERT models utilizing a custom sequential sampling strategy with two prompting strategies. We search in these samples for named entities and check if they are also present in the fine-tuning datasets. We experiment with two benchmark datasets in the domains of emails and blogs. We show that the application of DP has a detrimental effect on the text generation capabilities of BERT. Furthermore, we show that a fine-tuned BERT does not generate more named entities specific to the fine-tuning dataset than a BERT model that is pre-trained only. This suggests that BERT is unlikely to emit personal or privacy sensitive named entities. Overall, our results are important to understand to what extent BERT-based services are prone to training data extraction attacks.Comment: accepted at CD-MAKE 202

Reducing a Set of Regular Expressions and Analyzing Differences of Domain-specific Statistic Reporting

Due to the large amount of daily scientific publications, it is impossible to manually review each one. Therefore, an automatic extraction of key information is desirable. In this paper, we examine STEREO, a tool for extracting statistics from scientific papers using regular expressions. By adapting an existing regular expression inclusion algorithm for our use case, we decrease the number of regular expressions used in STEREO by about $33.8\%$. We reveal common patterns from the condensed rule set that can be used for the creation of new rules. We also apply STEREO, which was previously trained in the life-sciences and medical domain, to a new scientific domain, namely Human-Computer-Interaction (HCI), and re-evaluate it. According to our research, statistics in the HCI domain are similar to those in the medical domain, although a higher percentage of APA-conform statistics were found in the HCI domain. Additionally, we compare extraction on PDF and LaTeX source files, finding LaTeX to be more reliable for extraction