La transparencia y la no discriminación en el Estado de bienestar digital
Autores
-
Alberto Coddou Mc Manus, Dr.
Universidad Austral de Chile
https://orcid.org/0000-0003-2041-2304
-
Sebastián Smart Larraín, Dr.
Universidad Austral de Chile
https://orcid.org/0000-0003-3924-702X
Resumo
El uso intensivo y masivo de tecnologías digitales en la gestión y provisión de servicios, asistencia o programas sociales ha planteado diversos desafíos en materia de derechos humanos. Este trabajo se enfoca en los desafíos que la opacidad y la discriminación algorítmicas plantean al denominado Estado de bienestar digital. Desde esta perspectiva, el artículo pretende ser un aporte teórico en la creciente discusión sobre la gobernanza digital y su potencial distópico, cuestión que puede ser de interés para los debates que se darán en Chile, en particular, con respecto a los derechos sociales en el marco del proceso constituyente y a una futura política de inteligencia artificial.Palavras-chave:
Estado de bienestar digital, discriminación algorítmica, opacidad algorítmicaReferências
Adler, Matthew (2016). «A new Leviathan: Benefit sanctions in the twenty-first century». Journal of Law and Society, 43 (2): 195-227. DOI: 10.1111/j.1467-6478.2016.00749.x.
Alston, Phillip (2019). Estado de bienestar digital y derechos humanos. Informe del relator especial para extrema pobreza, A/74/48037. Disponible en https://bit.ly/3aDonxXht.
Ananny, Mike y Kate Crawford (2018). «Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability». New Media & Society, 20 (3): 973-989. DOI: 10.1177/1461444816676645.
Ashley, Kevin (2017). Artificial intelligence and legal analytics: New tools for law practice in the digital age. Cambridge: Cambridge University Press. DOI: 10.1017/9781316761380.
Atria, Fernando, Constanza Salgado y Javier Wilenmann (2020). El proceso constituyente en 138 preguntas y respuestas. Santiago: Lom.
Baeza-Yates, Ricardo (2018). «Bias on the Web». Communications of the ACM, 61 (6): 54-61. DOI: 10.1145/3209581.
Banco Mundial (2017). Big data in action for government: Big data innovation in public services, policy and engagement. World Bank Group. Disponible en https://bit.ly/2YU9BNP
Bovens, Mark (2007). «Analyzing and assessing accountability: A conceptual framework». European Law Journal, 13 (4): 447-468. DOI: 10.1111/j.1468-0386.2007.00378.x.
Boyd, Danah y Kate Crawford (2012). «Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon». Information Communication and Society, 15 (5): 662-679.DOI: 10.1080/1369118X.2012.678878.
Britton-Purdy, Jedediah, David Singh Grewal, Amy Kapczynski y K. Sabeel Rahman (2020). «Building a law-and-political-economy framework: Beyond the twentieth-century synthesis». The Yale Law Journal, 129 (6): 1.784-1.835. Disponible en https://bit.ly/3nc7pyg.
Burrell, Jena (2016). «How the machine ‘thinks’: Understanding opacity in machine learning algorithms». Big Data and Society, 3 (1). DOI: 10.1177/2053951715622512.
Citron, Danielle (2008). «Technological due process». Washington University Law Review, 85 (6): 1.249-1.313. Disponible en https://bit.ly/3con0Et.
Coddou Mc Manus, Alberto (2019). «La igualdad en la Constitución que queremos». En Jaime Bassa, Juan Carlos Ferrada y Cristián Viera (editores), La Constitución que queremos (157-194). Santiago: Lom.
Coglianese, Cary y David Lehr (2017). «Regulating by robot: Administrative decision making in the machine-learning era». Georgetown Law Journal, 105 (5): 1.147-1.223. Disponible en https://bit.ly/3Cu5SrF.
Crawford, Kate, Mary L. Gray, Kate Miltner (2014). «Critiquing big data: Politics, ethics, epistemology». International Journal of Communication, 8: 1.663-1.672. Disponible en https://bit.ly/3wZxDHp.
Dalton, Craig y Jim Thatcher (2014). «What does a critical data studies look like, and why do we care?», Society + Space. Disponible en https://bit.ly/3CmoR7q.
Dalton, Craig M., Linnet Taylor y Jim Thatcher (2016). «Critical Data Studies: A dialog on data and space». Big Data & Society, 3 (1). DOI:10.1177/2053951716648346.
Desai, Deven R. y Joshua A. Kroll (2017). «Trust but verify: A guide to algorithms and the law». Harvard Journal of Law & Technology, 31 (1): 1-64. Disponible en https://bit.ly/3nrJiM3.
Edwards, Lilian y Michael Veale (2017). «Slave to the algorithm? Why a right to explanation is probably not the remedy you are looking for». Duke Law & Technology Review, 16 (1): 18-34. Disponible en https://bit.ly/3clK5Ys.
Engelmann, Severin, Mo Chen, Felix Fischer, Ching-yu Kao y Jens Grossklags (2019). «Clear sanctions, vague rewards: How China’s social credit system currently defines ‘good’ and ‘bad’ behaviour». Proceedings of the Conference on fairness, accountability, and transparency (FAT* ‘19) Association for Computing Machinery (69-78), Nueva York. DOI: 10.1145/3287560.3287585.
Esping-Andersen, Gøsta (1990). The three worlds of welfare capitalism. Princeton University Press.
EU Commission (2020). Digital economy and society index (DESI). Human capital. Disponible en https://bit.ly/3jrkrnV.
Eubanks, Virginia (2018). Automating inequality: How high-tech tools profile, police and punish the poor. Londres: San Martin’s Press.
Fjeld, Jessica, Nele Achten, Hannah Hilligoss, Adam Nagy y Madhulika Srikumar (2020) «Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI», Berkman Klein Center for Internet & Society. Disponible en https://bit.ly/3aK89TP.
Figueroa, Pamela y Tomás Jordán (eds.) (2020). 7 propuestas para la nueva Constitución de Chile. Santiago: Editorial Usach.
Foucault, Michel (1976). Vigilar y castigar: El nacimiento de la prisión. Madrid: Siglo XXI.
Fredman, Sandra (2010). «Positive duties and socio-economic disadvantage: Bringing disadvantage onto the equality agenda». European Human Rights Law Review, 290 (3).
Gantchev, Valery (2019). «Data protection in the age of welfare conditionality: Respect for basic rights or a race to the bottom?». European Journal of Social Security, 21 (1): 3-22. DOI: 10.1177/1388262719838109.
Huber, Evelyne y Sara Niedzwiecki (2014). «Emerging welfare states in Latin America and East Asia». En Stephan Leibfried, Evelyne Huber, Matthew Lange, Jonah D. Levy y John D. Stephens (editores), The Oxford handbook of transformations of the state. Oxford: Oxford University Press. DOI: 10.1093/oxfordhb/9780199691586.013.43.
Kapczynski, Amy (2020). «The law of informational capitalism». Yale Law Journal 129 (5): 1.276-1.599.
King, Jeff (2019). «The future of social rights: Social rights as capstone». En Amartya Sen y Katherine Young (editores), The future of economic and social rights. Cambridge: Cambridge University Press.
Kitchin, Rob (2014). «Big Data, new epistemologies and paradigm shifts», Big Data & Society, 1 (1). DOI: 10.1177/2053951714528481.
Kitchin, Rob y Tracey P. Lauriault (2014). «Towards critical data studies: Charting and unpacking data assemblages and their work». En Josef Eckert, Andrew Shears y Jim Thatcher (editores), Thinking big data in geography. New regimes, new research. University of Nebraska Press.
Landau, David (2014). «The promise of a minimum core approach: The colombian model for judicial review of austerity measures». En Aoife Nolan (editor), Economic and social rights after the global financial crisis. Cambridge: Cambridge University Press.
Lazcoz, Guillermo y José Castillo Parrilla (2020). «Valoración algorítmica ante los derechos humanos y el Reglamento General de Protección de Datos: el caso SyRI». Revista Chilena de Derecho y Tecnología, 9 (1): 207-225. DOI: 10.5354/0719-2584.2020.56843.
Lundberg, Ema (2019). «Automated decision-making vs indirect discrimination: Solution or aggravation?». Independent written essay, master’s program in Constitutional Law and Human Rights, Umea University. Disponible en https://bit.ly/2N69gVm.
Laenen, Tijs, Bart Meuleman y Wim van Oorschot (editores) (2020). Welfare state legitimacy in times of crisis and austerity: Between continuity and change. Londres: Edward Elgar Publishing.
Marshall, Thomas H. y Thomas Bottomore (1998). Ciudadanía y clase social. Madrid: Alianza.
Mitchell, Margaret, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji y Timnit Gebru (2019). «Model cards for model reporting». Proceedings of the Conference on fairness, accountability, and transparency (FAT* ‘19) Association for Computing Machinery (220–229), Nueva York. DOI: 10.1145/3287560.3287596.
Morozov, Evgeny (2019). «Digital Socialism? The calculation debate in the age of big data». New Left Review, 116: 33-67. Disponible en https://bit.ly/32hKjOJ.
Muñoz, Catherine, Jeanna Neefe Matthews y Jorge Pérez (2021) «Sistemas de toma de decisiones automatizadas: ¿De qué hablamos cuando hablamos de transparencia y del derecho a una explicación?». Bits de Ciencia, 21: 27-36. Disponible en https://bit.ly/3FsRfXi.
O’Cinneide, Colm (2014). «Austerity and the faded dream of a ‘social Europe’». En Aoife Nolan (editor), Economic and social rights after the global financial crisis. Cambridge University Press. DOI: 10.1017/CBO9781107337954.010.
Pasquale, Frank (2015). The black box society: The secret algorithms that control money and information. Boston: Harvard University.
Puschmann, Cornelius y Jean Burgess (2014). Big data, big questions: Metaphors of big data». International Journal of Communication, 8: 1.690-1.709. Disponible en https://bit.ly/3kMjZ5z.
Redden, Joanna (2018). «Democratic governance in an age of datafication: Lessons from mapping government discourses and practices». Big Data & Society, 5 (2). DOI: 10.1177/2053951718809145.
Rieder, Gernot y Judith Simon (2016). «Datatrust: Or, the political quest for numerical evidence and the epistemologies of big data». Big Data & Society, 3 (1). DOI: 10.1177/2053951716649398.
Rieke, Aaron, Miranda Bogen y David Robinson (2018). «Public scrutiny of automated decisions: Early lessons and emerging methods. An Upturn and Omidyar Network report». Disponible en https://bit.ly/3np3uxU.
Robinson, David y Alex Rosenblat (2020). «Governing an algorithm in the wild». Data & Society. Disponible en https://bit.ly/3ry7eN1.
Ronconi, Liliana (2018). «Repensando el principio de igualdad: alcances de la igualdad real». Isonomía, 49. DOI: 10.5347/49.2018.
Ruiz, Carlos (2020). Octubre chileno. La irrupción de un nuevo pueblo. Santiago: Taurus.
Schartum, Dag W (2016). «Law and algorithms in the public domain». Nordic Journal of Applied Ethics, 1: 15-26. DOI: 10.5324/eip.v10i1.1973.
Sills, Arthur. (1970). «Automated data processing and the issue of privacy». Seton Hall Law Review, 1.
Smith, Gavin J.D. (2020). «The politics of algorithmic governance in the black box city». Big Data & Society, 7 (2). DOI: 10.1177/2053951720933989.
Tversky, Amos y Daniel Kahneman (1974). «Judgment under uncertainty: Heuristics and biases». Science, 185 (4.157): 1124-1131. DOI: 10.1126/science.185.4157.1124.
Viera Álvarez, Cristián (2014). «Estado social como fórmula en la constitución chilena». Revista de Derecho (Universidad Católica del Norte), 21 (2): 453-482. DOI: 10.4067/S0718-97532014000200014.
Viljoen, Salome (en prensa). «Democratic data: A relational theory for data governance». Yale Law Journal. Disponible en https://bit.ly/3CX7gmL.
Wachter, Sandra, Brent Mittelstadt y Luciano Floridi (2017). «Why a right to explanation of automated decision-making does not exist in the general data protection regulation». International Data Privacy Law, 7 (2): 76-99. DOI: 10.1093/idpl/ipx005.
Watts, Beth y Suzanne Fitzpatrick (2018). Welfare conditionality. Londres: Routledge.
West, Sarah M., Meredith Whittaker y Kate Crawford (2019). Discriminating systems: Gender, race and power in AI. AI Now Institute. Disponible en https://bit.ly/2YVyNXK.
Zuboff, Shoshana (2020). La era del capitalismo de la vigilancia. Barcelona: Ediciones Paidós.
Zuiderveen Borgesius, Frederik J. (2019). «Strengthening legal protection against discrimination by algorithms and artificial intelligence». The International Journal of Human Rights, 24 (10): 1572-1593. DOI: 10.1080/13642987.2020.1743976.
Alston, Phillip (2019). Estado de bienestar digital y derechos humanos. Informe del relator especial para extrema pobreza, A/74/48037. Disponible en https://bit.ly/3aDonxXht.
Ananny, Mike y Kate Crawford (2018). «Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability». New Media & Society, 20 (3): 973-989. DOI: 10.1177/1461444816676645.
Ashley, Kevin (2017). Artificial intelligence and legal analytics: New tools for law practice in the digital age. Cambridge: Cambridge University Press. DOI: 10.1017/9781316761380.
Atria, Fernando, Constanza Salgado y Javier Wilenmann (2020). El proceso constituyente en 138 preguntas y respuestas. Santiago: Lom.
Baeza-Yates, Ricardo (2018). «Bias on the Web». Communications of the ACM, 61 (6): 54-61. DOI: 10.1145/3209581.
Banco Mundial (2017). Big data in action for government: Big data innovation in public services, policy and engagement. World Bank Group. Disponible en https://bit.ly/2YU9BNP
Bovens, Mark (2007). «Analyzing and assessing accountability: A conceptual framework». European Law Journal, 13 (4): 447-468. DOI: 10.1111/j.1468-0386.2007.00378.x.
Boyd, Danah y Kate Crawford (2012). «Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon». Information Communication and Society, 15 (5): 662-679.DOI: 10.1080/1369118X.2012.678878.
Britton-Purdy, Jedediah, David Singh Grewal, Amy Kapczynski y K. Sabeel Rahman (2020). «Building a law-and-political-economy framework: Beyond the twentieth-century synthesis». The Yale Law Journal, 129 (6): 1.784-1.835. Disponible en https://bit.ly/3nc7pyg.
Burrell, Jena (2016). «How the machine ‘thinks’: Understanding opacity in machine learning algorithms». Big Data and Society, 3 (1). DOI: 10.1177/2053951715622512.
Citron, Danielle (2008). «Technological due process». Washington University Law Review, 85 (6): 1.249-1.313. Disponible en https://bit.ly/3con0Et.
Coddou Mc Manus, Alberto (2019). «La igualdad en la Constitución que queremos». En Jaime Bassa, Juan Carlos Ferrada y Cristián Viera (editores), La Constitución que queremos (157-194). Santiago: Lom.
Coglianese, Cary y David Lehr (2017). «Regulating by robot: Administrative decision making in the machine-learning era». Georgetown Law Journal, 105 (5): 1.147-1.223. Disponible en https://bit.ly/3Cu5SrF.
Crawford, Kate, Mary L. Gray, Kate Miltner (2014). «Critiquing big data: Politics, ethics, epistemology». International Journal of Communication, 8: 1.663-1.672. Disponible en https://bit.ly/3wZxDHp.
Dalton, Craig y Jim Thatcher (2014). «What does a critical data studies look like, and why do we care?», Society + Space. Disponible en https://bit.ly/3CmoR7q.
Dalton, Craig M., Linnet Taylor y Jim Thatcher (2016). «Critical Data Studies: A dialog on data and space». Big Data & Society, 3 (1). DOI:10.1177/2053951716648346.
Desai, Deven R. y Joshua A. Kroll (2017). «Trust but verify: A guide to algorithms and the law». Harvard Journal of Law & Technology, 31 (1): 1-64. Disponible en https://bit.ly/3nrJiM3.
Edwards, Lilian y Michael Veale (2017). «Slave to the algorithm? Why a right to explanation is probably not the remedy you are looking for». Duke Law & Technology Review, 16 (1): 18-34. Disponible en https://bit.ly/3clK5Ys.
Engelmann, Severin, Mo Chen, Felix Fischer, Ching-yu Kao y Jens Grossklags (2019). «Clear sanctions, vague rewards: How China’s social credit system currently defines ‘good’ and ‘bad’ behaviour». Proceedings of the Conference on fairness, accountability, and transparency (FAT* ‘19) Association for Computing Machinery (69-78), Nueva York. DOI: 10.1145/3287560.3287585.
Esping-Andersen, Gøsta (1990). The three worlds of welfare capitalism. Princeton University Press.
EU Commission (2020). Digital economy and society index (DESI). Human capital. Disponible en https://bit.ly/3jrkrnV.
Eubanks, Virginia (2018). Automating inequality: How high-tech tools profile, police and punish the poor. Londres: San Martin’s Press.
Fjeld, Jessica, Nele Achten, Hannah Hilligoss, Adam Nagy y Madhulika Srikumar (2020) «Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI», Berkman Klein Center for Internet & Society. Disponible en https://bit.ly/3aK89TP.
Figueroa, Pamela y Tomás Jordán (eds.) (2020). 7 propuestas para la nueva Constitución de Chile. Santiago: Editorial Usach.
Foucault, Michel (1976). Vigilar y castigar: El nacimiento de la prisión. Madrid: Siglo XXI.
Fredman, Sandra (2010). «Positive duties and socio-economic disadvantage: Bringing disadvantage onto the equality agenda». European Human Rights Law Review, 290 (3).
Gantchev, Valery (2019). «Data protection in the age of welfare conditionality: Respect for basic rights or a race to the bottom?». European Journal of Social Security, 21 (1): 3-22. DOI: 10.1177/1388262719838109.
Huber, Evelyne y Sara Niedzwiecki (2014). «Emerging welfare states in Latin America and East Asia». En Stephan Leibfried, Evelyne Huber, Matthew Lange, Jonah D. Levy y John D. Stephens (editores), The Oxford handbook of transformations of the state. Oxford: Oxford University Press. DOI: 10.1093/oxfordhb/9780199691586.013.43.
Kapczynski, Amy (2020). «The law of informational capitalism». Yale Law Journal 129 (5): 1.276-1.599.
King, Jeff (2019). «The future of social rights: Social rights as capstone». En Amartya Sen y Katherine Young (editores), The future of economic and social rights. Cambridge: Cambridge University Press.
Kitchin, Rob (2014). «Big Data, new epistemologies and paradigm shifts», Big Data & Society, 1 (1). DOI: 10.1177/2053951714528481.
Kitchin, Rob y Tracey P. Lauriault (2014). «Towards critical data studies: Charting and unpacking data assemblages and their work». En Josef Eckert, Andrew Shears y Jim Thatcher (editores), Thinking big data in geography. New regimes, new research. University of Nebraska Press.
Landau, David (2014). «The promise of a minimum core approach: The colombian model for judicial review of austerity measures». En Aoife Nolan (editor), Economic and social rights after the global financial crisis. Cambridge: Cambridge University Press.
Lazcoz, Guillermo y José Castillo Parrilla (2020). «Valoración algorítmica ante los derechos humanos y el Reglamento General de Protección de Datos: el caso SyRI». Revista Chilena de Derecho y Tecnología, 9 (1): 207-225. DOI: 10.5354/0719-2584.2020.56843.
Lundberg, Ema (2019). «Automated decision-making vs indirect discrimination: Solution or aggravation?». Independent written essay, master’s program in Constitutional Law and Human Rights, Umea University. Disponible en https://bit.ly/2N69gVm.
Laenen, Tijs, Bart Meuleman y Wim van Oorschot (editores) (2020). Welfare state legitimacy in times of crisis and austerity: Between continuity and change. Londres: Edward Elgar Publishing.
Marshall, Thomas H. y Thomas Bottomore (1998). Ciudadanía y clase social. Madrid: Alianza.
Mitchell, Margaret, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji y Timnit Gebru (2019). «Model cards for model reporting». Proceedings of the Conference on fairness, accountability, and transparency (FAT* ‘19) Association for Computing Machinery (220–229), Nueva York. DOI: 10.1145/3287560.3287596.
Morozov, Evgeny (2019). «Digital Socialism? The calculation debate in the age of big data». New Left Review, 116: 33-67. Disponible en https://bit.ly/32hKjOJ.
Muñoz, Catherine, Jeanna Neefe Matthews y Jorge Pérez (2021) «Sistemas de toma de decisiones automatizadas: ¿De qué hablamos cuando hablamos de transparencia y del derecho a una explicación?». Bits de Ciencia, 21: 27-36. Disponible en https://bit.ly/3FsRfXi.
O’Cinneide, Colm (2014). «Austerity and the faded dream of a ‘social Europe’». En Aoife Nolan (editor), Economic and social rights after the global financial crisis. Cambridge University Press. DOI: 10.1017/CBO9781107337954.010.
Pasquale, Frank (2015). The black box society: The secret algorithms that control money and information. Boston: Harvard University.
Puschmann, Cornelius y Jean Burgess (2014). Big data, big questions: Metaphors of big data». International Journal of Communication, 8: 1.690-1.709. Disponible en https://bit.ly/3kMjZ5z.
Redden, Joanna (2018). «Democratic governance in an age of datafication: Lessons from mapping government discourses and practices». Big Data & Society, 5 (2). DOI: 10.1177/2053951718809145.
Rieder, Gernot y Judith Simon (2016). «Datatrust: Or, the political quest for numerical evidence and the epistemologies of big data». Big Data & Society, 3 (1). DOI: 10.1177/2053951716649398.
Rieke, Aaron, Miranda Bogen y David Robinson (2018). «Public scrutiny of automated decisions: Early lessons and emerging methods. An Upturn and Omidyar Network report». Disponible en https://bit.ly/3np3uxU.
Robinson, David y Alex Rosenblat (2020). «Governing an algorithm in the wild». Data & Society. Disponible en https://bit.ly/3ry7eN1.
Ronconi, Liliana (2018). «Repensando el principio de igualdad: alcances de la igualdad real». Isonomía, 49. DOI: 10.5347/49.2018.
Ruiz, Carlos (2020). Octubre chileno. La irrupción de un nuevo pueblo. Santiago: Taurus.
Schartum, Dag W (2016). «Law and algorithms in the public domain». Nordic Journal of Applied Ethics, 1: 15-26. DOI: 10.5324/eip.v10i1.1973.
Sills, Arthur. (1970). «Automated data processing and the issue of privacy». Seton Hall Law Review, 1.
Smith, Gavin J.D. (2020). «The politics of algorithmic governance in the black box city». Big Data & Society, 7 (2). DOI: 10.1177/2053951720933989.
Tversky, Amos y Daniel Kahneman (1974). «Judgment under uncertainty: Heuristics and biases». Science, 185 (4.157): 1124-1131. DOI: 10.1126/science.185.4157.1124.
Viera Álvarez, Cristián (2014). «Estado social como fórmula en la constitución chilena». Revista de Derecho (Universidad Católica del Norte), 21 (2): 453-482. DOI: 10.4067/S0718-97532014000200014.
Viljoen, Salome (en prensa). «Democratic data: A relational theory for data governance». Yale Law Journal. Disponible en https://bit.ly/3CX7gmL.
Wachter, Sandra, Brent Mittelstadt y Luciano Floridi (2017). «Why a right to explanation of automated decision-making does not exist in the general data protection regulation». International Data Privacy Law, 7 (2): 76-99. DOI: 10.1093/idpl/ipx005.
Watts, Beth y Suzanne Fitzpatrick (2018). Welfare conditionality. Londres: Routledge.
West, Sarah M., Meredith Whittaker y Kate Crawford (2019). Discriminating systems: Gender, race and power in AI. AI Now Institute. Disponible en https://bit.ly/2YVyNXK.
Zuboff, Shoshana (2020). La era del capitalismo de la vigilancia. Barcelona: Ediciones Paidós.
Zuiderveen Borgesius, Frederik J. (2019). «Strengthening legal protection against discrimination by algorithms and artificial intelligence». The International Journal of Human Rights, 24 (10): 1572-1593. DOI: 10.1080/13642987.2020.1743976.
