LEADER 04176nam 2200505z- 450 001 9910504307703321 005 20230519161733.0 010 $a2-37496-129-X 035 $a(CKB)5590000000629394 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/72296 035 $a(EXLCZ)995590000000629394 100 $a20202102d2020 |y 0 101 0 $afre 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAnfractuosités de la fiction$eInscriptions du politique dans la littérature hispanophone contemporaine 210 $aReims$cEPURE, Éditions et presses universitaires de Reims$d2020 215 $a1 electronic resource (312 p.) 225 1 $aSaxifrages 311 $a2-37496-128-1 330 $aThis book brings together ten contributions from French and foreign specialists whose research and work focus on contemporary Spanish-language literature. They analyse the ways in which certain historical events, violence, memory, and political activism find their way into the narrative device in order to make it politically singular. They explore these relationships in a variety of ways, from an interdisciplinary perspective, at the crossroads of literature, philosophy, cinema and contemporary history. Ce volume qui inaugure la collection Saxifrages interroge et met en relation aussi bien les champs de la poétique, du politique et de l?éthique que le travail de la fiction. Car la fiction, à l?instar de la métaphore vive, désocculte les structures profondes de la réalité auxquelles nous sommes reliés en tant que mortels (Ric?ur) et élabore un système d?évidences sensibles qui donne à voir l?existence (Rancière). Le constat d?un retour au réel ? voire à une certaine forme de réalisme ? dans la littérature contemporaine des dernières décennies réactualise ces réflexions et approches du travail de la fiction et des images en tant qu?objets esthétiques capables de faire sens et de réinventer notre imaginaire politique (Didi­ Huberman). Comment la littérature procède-­t-­elle lorsqu?elle n?est plus censée refléter comme le miroir stendhalien la réalité ? Comment traiter le politique faufilé dans la fiction lorsqu?il ne s?agit plus de le représenter « simplement » ? Car lire le politique, en traquer les traces qui se glissent entre les failles et fissures d?un champ social ou artistique pour ?uvrer de l?intérieur en craquelant ? comme le font les forces faibles des saxifrages ? les systèmes clos et « parfaits », c?est appréhender cette faculté de faire sens, de fictionner. On trouvera réunies ici dix contributions de spécialistes français et étrangers dont la recherche et les travaux portent sur la littérature hispanophone contemporaine. Ils analysent les manières dont certains événements historiques, la violence, la mémoire, l?engagement se faufilent dans le dispositif narratif pour le singulariser politiquement. Ils explorent ces rapports sous des aspects les plus divers, dans une perspective interdisciplinaire, à la croisée de la littérature, la philosophie, le cinéma, l?histoire contemporaine. 517 $aAnfractuositÃs de la fiction 517 $aAnfractuosités de la fiction 606 $aPopular culture$2bicssc 606 $aCivil rights & citizenship$2bicssc 606 $aFreedom of information & freedom of speech$2bicssc 606 $aLiterary studies: from c 1900 -$2bicssc 606 $aLatin-American Spanish$2bicssc 606 $aLatin America$2bicssc 610 $aSpanish-speaking literature 610 $aPolitics and literature 615 7$aPopular culture 615 7$aCivil rights & citizenship 615 7$aFreedom of information & freedom of speech 615 7$aLiterary studies: from c 1900 - 615 7$aLatin-American Spanish 615 7$aLatin America 700 $aWALDEGARAY$b Marta Inés$4edt$01288606 702 $aWALDEGARAY$b Marta Inés$4oth 906 $aBOOK 912 $a9910504307703321 996 $aAnfractuosités de la fiction$93020913 997 $aUNINA LEADER 05160nam 22006735 450 001 9910619276703321 005 20230810175633.0 010 $a9783031093678$b(electronic bk.) 010 $z9783031093661 024 7 $a10.1007/978-3-031-09367-8 035 $a(MiAaPQ)EBC7120435 035 $a(Au-PeEL)EBL7120435 035 $a(CKB)25181489400041 035 $a(DE-He213)978-3-031-09367-8 035 $a(PPN)26585752X 035 $a(EXLCZ)9925181489400041 100 $a20221020d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data, Algorithms and Food Safety $eA Legal and Ethical Approach to Data Ownership and Data Governance /$fby Salvatore Sapienza 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (225 pages) 225 1 $aLaw, Governance and Technology Series,$x2352-1910 ;$v52 311 08$aPrint version: Sapienza, Salvatore Big Data, Algorithms and Food Safety Cham : Springer International Publishing AG,c2022 9783031093661 320 $aIncludes bibliographical references. 327 $aChapter 1:Food, Big Data, Artificial Intelligence -- Chapter 2:Data Ownership in Food-related Information -- Chapter 3:Food Consumption Data Protection -- Chapter 4:Current and Foreseeable Trends in Food Safety Data Governance -- Chapter 5: The P-SAFETY Model: a Unifying Ethical Approach -- Chapter 6: Conclusion: a Responsible Food Innovation. 330 $aThis book identifies the principles that should be applied when processing Big Data in the context of food safety risk assessments. Food safety is a critical goal in the protection of individuals? right to health and the flourishing of the food and feed market. Big Data is fostering new applications capable of enhancing the accuracy of food safety risk assessments. An extraordinary amount of information is analysed to detect the existence or predict the likelihood of future risks, also by means of machine learning algorithms. Big Data and novel analysis techniques are topics of growing interest for food safety agencies, including the European Food Safety Authority (EFSA). This wealth of information brings with it both opportunities and risks concerning the extraction of meaningful inferences from data. However, conflicting interests and tensions among the parties involved are hindering efforts to find shared methods for steering the processing of Big Data in a sound, transparent and trustworthy way. While consumers call for more transparency, food business operators tend to be reluctant to share informational assets. This has resulted in a considerable lack of trust in the EU food safety system. A recent legislative reform, supported by new legal cases, aims to restore confidence in the risk analysis system by reshaping the meaning of data ownership in this domain. While this regulatory approach is being established, breakthrough analytics techniques are encouraging thinking about the next steps in managing food safety data in the age of machine learning. The book focuses on two core topics ? data ownership and data governance ? by evaluating how the regulatory framework addresses the challenges raised by Big Data and its analysis in an applied, significant, and overlooked domain. To do so, it adopts an interdisciplinary approach that considers both the technological advances and the policy tools adopted in the European Union, while also assuming an ethical perspective when exploring potential solutions. The conclusion puts forward a proposal: an ethical blueprint for identifying the principles ? Security, Accountability, Fairness, Explainability, Transparency and Privacy ? to be observed when processing Big Data for food safety purposes, including by means of machine learning. Possible implementations are then discussed, also in connection with two recent legislative proposals, namely the Data Governance Act and the Artificial Intelligence Act. 410 0$aLaw, Governance and Technology Series,$x2352-1910 ;$v52 606 $aInformation technology$xLaw and legislation 606 $aMass media$xLaw and legislation 606 $aArtificial intelligence 606 $aBig data 606 $aFood$xSafety measures 606 $aIT Law, Media Law, Intellectual Property 606 $aArtificial Intelligence 606 $aBig Data 606 $aFood Safety 615 0$aInformation technology$xLaw and legislation. 615 0$aMass media$xLaw and legislation. 615 0$aArtificial intelligence. 615 0$aBig data. 615 0$aFood$xSafety measures. 615 14$aIT Law, Media Law, Intellectual Property. 615 24$aArtificial Intelligence. 615 24$aBig Data. 615 24$aFood Safety. 676 $a005.7 676 $a005.7 700 $aSapienza$b Salvatore$01262886 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910619276703321 996 $aBig Data, Algorithms and Food Safety$92954919 997 $aUNINA