1. Critica de capire e altri scritti. 2. Scritti kantiani. 3. L'analitica trascendentale. 4. Il problema della scienza e il giudizio storico.

In December 2017, Law 219/2017, ‘Provisions for informed consent and advance directives’, was approved in Italy. The law is the culmination of a year-long process and the subject of heated debate throughout Italian society. Contentious issues are addressed in the law. What emerges clearly are concepts such as quality of life, autonomy, and the right to accept or refuse any medical treatment – concepts that should be part of an optimal relationship between the patient and healthcare professionals. The law maximizes (...) the value of the patient’s time to decide. Every patient is allowed to make choices for the present as well as for the future, conceived as a continuation of the present, and to decide what comes next, based on what he/she already knows. The law identifies three distinct but converging paths towards the affirmation of a care relationship based on reciprocal trust and respect: the possibility to consent to or refuse treatment, the shared care planning, and advance directives. The fundamental point to emerge from the new Italian law is that consensus is an essential connotation of the treatment relationship. Consensus is not limited to the acceptance/rejection of medical treatment but is ongoing. It is projected into the future through shared care planning and advance directives which act as tools for self-determination and the manifestation of the beliefs and preferences of persons unable to express their will. These principles are in line with the idea of appropriate care as evaluated from two different perspectives, one of scientific adequacy and the other commensurate with the individual’s resources, fragility, values, and beliefs. Surely, however, the new law is not the end of the matter on issues such as conscientious objection, which is deeply rooted within the Italian cultural and political debate. In this regard, healthcare institutions and policymakers will be called upon to develop and implement organizational policies aimed at the management of foreseeable conscientious objection in this field. (shrink)

Ontologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal ontologies (...) and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated. (shrink)

Ontologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal ontologies (...) and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated. (shrink)

Ontologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal ontologies (...) and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated. (shrink)

This paper describes the Eunomos software, an advanced legal document and knowledge management system, based on legislative XML and ontologies. We describe the challenges of legal research in an increasingly complex, multi-level and multi-lingual world and how the Eunomos software helps users cut through the information overload to get the legal information they need in an organized and structured way and keep track of the state of the relevant law on any given topic. Using NLP tools to semi-automate the lower-skill (...) tasks makes this ambitious project a realistic commercial prospect as it helps keep costs down while at the same time allowing greater coverage. We describe the core system from workflow and technical perspectives, and discuss applications of the system for various user groups. (shrink)

The author makes an innovative reading of human rights based on the dimensions of space, time and memory, as constituent dimensions of being. To do this, he explains new coordinates in the post-human era of the globalized world.: the profound crisis of political space revealed in the State, and its..

The automated identification of national implementations of European directives by text similarity techniques has shown promising preliminary results. Previous works have proposed and utilized unsupervised lexical and semantic similarity techniques based on vector space models, latent semantic analysis and topic models. However, these techniques were evaluated on a small multilingual corpus of directives and NIMs. In this paper, we utilize word and paragraph embedding models learned by shallow neural networks from a multilingual legal corpus of European directives and national legislation (...) to develop unsupervised semantic similarity systems to identify transpositions. We evaluate these models and compare their results with the previous unsupervised methods on a multilingual test corpus of 43 Directives and their corresponding NIMs. We also develop supervised machine learning models to identify transpositions and compare their performance with different feature sets. (shrink)

The automated identification of national implementations of European directives by text similarity techniques has shown promising preliminary results. Previous works have proposed and utilized unsupervised lexical and semantic similarity techniques based on vector space models, latent semantic analysis and topic models. However, these techniques were evaluated on a small multilingual corpus of directives and NIMs. In this paper, we utilize word and paragraph embedding models learned by shallow neural networks from a multilingual legal corpus of European directives and national legislation (...) to develop unsupervised semantic similarity systems to identify transpositions. We evaluate these models and compare their results with the previous unsupervised methods on a multilingual test corpus of 43 Directives and their corresponding NIMs. We also develop supervised machine learning models to identify transpositions and compare their performance with different feature sets. (shrink)

Every organization has to deal with operational risks, arising from the execution of a company’s primary business functions. In this paper, we describe a legal knowledge management system which helps users understand the meaning of legislative text and the relationship between norms. While much of the knowledge requires the input of legal experts, we focus in this article on NLP applications that semi-automate essential time-consuming and lower-skill tasks—classifying legal documents, identifying cross-references and legislative amendments, linking legal terms to the most (...) relevant definitions, and extracting key elements of legal provisions to facilitate clarity and advanced search options. The use of Natural Language Processing tools to semi-automate such tasks makes the proposal a realistic commercial prospect as it helps keep costs down while allowing greater coverage. (shrink)

Every organization has to deal with operational risks, arising from the execution of a company’s primary business functions. In this paper, we describe a legal knowledge management system which helps users understand the meaning of legislative text and the relationship between norms. While much of the knowledge requires the input of legal experts, we focus in this article on NLP applications that semi-automate essential time-consuming and lower-skill tasks—classifying legal documents, identifying cross-references and legislative amendments, linking legal terms to the most (...) relevant definitions, and extracting key elements of legal provisions to facilitate clarity and advanced search options. The use of Natural Language Processing tools to semi-automate such tasks makes the proposal a realistic commercial prospect as it helps keep costs down while allowing greater coverage. (shrink)

Per una sociosemiotica della comunicazione musicale -- Per una sociosemiotica dei generi musicali -- Per una sociosemiotica della novità in musica -- Per una sociosemiotica del dubstep.

1. La conoscenza -- 2. Dio -- 3. La natura -- 4. L'uomo.

This article seeks to address the problem of the ‘resource consumption bottleneck’ of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in a legal document management system.