Subjects -> POLITICAL SCIENCE (Total: 1097 journals)
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    - INTERNATIONAL RELATIONS (148 journals)
    - POLITICAL SCIENCE (898 journals)
    - POLITICAL SCIENCES: GENERAL (35 journals)

POLITICAL SCIENCE (898 journals)                  1 2 3 4 5 | Last

Showing 1 - 200 of 281 Journals sorted alphabetically
A Contracorriente     Open Access   (Followers: 3)
Ab Imperio     Full-text available via subscription   (Followers: 4)
Acciones e Investigaciones Sociales     Open Access   (Followers: 1)
ACME : An International Journal for Critical Geographies     Open Access  
Acta Borealia: A Nordic Journal of Circumpolar Societies     Hybrid Journal   (Followers: 1)
Acta Politica Estica     Open Access   (Followers: 1)
Acta Universitatis Sapientiae, European and Regional Studies     Open Access  
Administory. Zeitschrift für Verwaltungsgeschichte     Open Access   (Followers: 1)
Administrative Science Quarterly     Full-text available via subscription   (Followers: 151)
AFFRIKA Journal of Politics, Economics and Society     Full-text available via subscription   (Followers: 4)
Africa Conflict Monitor     Full-text available via subscription   (Followers: 7)
Africa Insight     Full-text available via subscription   (Followers: 14)
Africa Intelligence     Full-text available via subscription   (Followers: 14)
Africa Renewal     Free   (Followers: 13)
Africa Today     Full-text available via subscription   (Followers: 23)
African Affairs     Hybrid Journal   (Followers: 68)
African Conflict and Peacebuilding Review     Full-text available via subscription   (Followers: 16)
African Diaspora     Open Access   (Followers: 10)
African East-Asian Affairs     Open Access   (Followers: 10)
African Identities     Hybrid Journal   (Followers: 15)
African Journal of Democracy and Governance     Full-text available via subscription   (Followers: 3)
African Journal of Rhetoric     Full-text available via subscription   (Followers: 3)
African Renaissance     Full-text available via subscription   (Followers: 4)
African Yearbook of Rhetoric     Full-text available via subscription   (Followers: 3)
Africa’s Public Service Delivery and Performance Review     Open Access   (Followers: 5)
Afrika Focus     Open Access  
Afrique contemporaine : La revue de l'Afrique et du développement     Full-text available via subscription   (Followers: 2)
Agenda Internacional     Open Access  
Agenda Política     Open Access   (Followers: 1)
Agenda: A Journal of Policy Analysis and Reform     Full-text available via subscription   (Followers: 3)
Agrarian South : Journal of Political Economy     Hybrid Journal   (Followers: 2)
Akademik Hassasiyetler     Open Access  
Akademik Yaklaşımlar Dergisi     Open Access   (Followers: 1)
Alternatives : Global, Local, Political     Hybrid Journal   (Followers: 10)
América Latina Hoy     Open Access   (Followers: 2)
American Communist History     Hybrid Journal   (Followers: 19)
American Enterprise Institute     Free   (Followers: 3)
American Foreign Policy Interests: The Journal of the National Committee on American Foreign Policy     Hybrid Journal   (Followers: 8)
American Journal of Political Science     Hybrid Journal   (Followers: 259)
American Political Science Review     Hybrid Journal   (Followers: 264)
American Political Thought     Full-text available via subscription   (Followers: 13)
American Politics Research     Hybrid Journal   (Followers: 30)
American Quarterly     Full-text available via subscription   (Followers: 24)
Anacronismo e Irrupción     Open Access  
Anais Eletrônicos do Congresso Epistemologias do Sul     Open Access  
Análise Social     Open Access   (Followers: 4)
Ankara University SBF Journal     Open Access   (Followers: 1)
Annales Universitatis Mariae Curie-Sklodowska, sectio M – Balcaniensis et Carpathiensis     Open Access  
Annals of the American Academy of Political and Social Science     Hybrid Journal   (Followers: 44)
Annual Review of Economics     Full-text available via subscription   (Followers: 43)
Annual Review of Political Science     Full-text available via subscription   (Followers: 140)
Anuario Latinoamericano : Ciencias Políticas y Relaciones Internacionales     Open Access  
AQ - Australian Quarterly     Full-text available via subscription  
Arabian Humanities     Open Access   (Followers: 6)
Arctic Review on Law and Politics     Open Access   (Followers: 1)
Arena Journal     Full-text available via subscription   (Followers: 1)
Armed Conflict Survey     Full-text available via subscription   (Followers: 12)
Asia & the Pacific Policy Studies     Open Access   (Followers: 14)
Asia and the Global Economy     Open Access  
Asia Policy     Full-text available via subscription   (Followers: 6)
Asia-Pacific Journal : Japan Focus     Open Access   (Followers: 11)
Asia-Pacific Journal of Regional Science     Hybrid Journal   (Followers: 1)
Asia-Pacific Review     Hybrid Journal   (Followers: 15)
Asian Affairs: An American Review     Hybrid Journal   (Followers: 1)
Asian Journal of Comparative Politics     Hybrid Journal   (Followers: 3)
Asian Journal of Political Science     Hybrid Journal   (Followers: 20)
Asian Politics and Policy     Hybrid Journal   (Followers: 8)
Astropolitics: The International Journal of Space Politics & Policy     Hybrid Journal   (Followers: 13)
AUDEM : The International Journal of Higher Education and Democracy     Full-text available via subscription   (Followers: 12)
Audens : revista estudiantil d'anàlisi interdisciplinària     Open Access  
Australasian Review of African Studies, The     Full-text available via subscription   (Followers: 2)
Australian Journal of International Affairs     Hybrid Journal   (Followers: 15)
Australian Journal of Political Science     Hybrid Journal   (Followers: 14)
Austrian Journal of South-East Asian Studies     Open Access  
Balcanica Posnaniensia Acta et studia     Open Access  
Baltic Journal of Political Science     Open Access   (Followers: 1)
Bandung : Journal of the Global South     Open Access   (Followers: 1)
Behavioral Sciences of Terrorism and Political Aggression     Hybrid Journal   (Followers: 36)
Beleid en Maatschappij     Full-text available via subscription   (Followers: 1)
BMC International Health and Human Rights     Open Access   (Followers: 9)
Bohemistyka     Open Access  
Boletim Meridiano 47 : Journal of Global Studies     Open Access  
Borderlands Journal : Culture, Politics, Law and Earth     Open Access   (Followers: 1)
Brazilian Political Science Review     Open Access   (Followers: 5)
Brésil(s)     Open Access  
British Journal of Canadian Studies     Hybrid Journal   (Followers: 12)
British Journal of Political Science     Hybrid Journal   (Followers: 177)
British Journal of Politics and International Relations     Hybrid Journal   (Followers: 35)
British Politics     Hybrid Journal   (Followers: 13)
British Review of New Zealand Studies     Full-text available via subscription   (Followers: 2)
Brookings Papers on Economic Activity     Open Access   (Followers: 68)
Bulletin d'histoire politique     Full-text available via subscription   (Followers: 4)
Cadernos de Estudos Sociais e Políticos     Open Access   (Followers: 2)
Cadernos de Ética e Filosofia Política     Open Access  
Cahiers de l'Urmis     Open Access   (Followers: 1)
Cahiers de Sciences politiques de l'ULg     Open Access   (Followers: 1)
California Journal of Politics and Policy     Open Access   (Followers: 2)
Cambio 16     Full-text available via subscription   (Followers: 5)
Cambio : Rivista sulle Trasformazioni Sociali     Open Access  
Cambridge Review of International Affairs     Hybrid Journal   (Followers: 23)
Canadian Foreign Policy Journal     Hybrid Journal   (Followers: 7)
Canadian Journal of European and Russian Studies     Open Access   (Followers: 1)
Canadian Journal of Political Science/Revue canadienne de science politique     Full-text available via subscription   (Followers: 24)
Caucasus Survey     Hybrid Journal   (Followers: 1)
Central and Eastern European Review     Open Access   (Followers: 4)
Central Asian Affairs     Hybrid Journal   (Followers: 2)
Central Banking     Full-text available via subscription   (Followers: 7)
Central European Journal of Public Policy     Open Access   (Followers: 3)
China : An International Journal     Full-text available via subscription   (Followers: 20)
China International Strategy Review     Hybrid Journal   (Followers: 2)
China perspectives     Open Access   (Followers: 12)
China Quarterly     Hybrid Journal   (Followers: 60)
China Report     Hybrid Journal   (Followers: 11)
China Review International     Full-text available via subscription   (Followers: 11)
China-EU Law Journal     Hybrid Journal   (Followers: 5)
Chinese Journal of Global Governance     Open Access   (Followers: 1)
Chinese Journal of International Politics     Hybrid Journal   (Followers: 12)
Chinese Political Science Review     Hybrid Journal   (Followers: 3)
Chinese Studies     Open Access   (Followers: 4)
Citizenship Education Research Journal (CERJ)     Open Access   (Followers: 1)
Cittadinanza Europea (LA)     Full-text available via subscription   (Followers: 1)
Civil Wars     Hybrid Journal   (Followers: 21)
Claremont-UC Undergraduate Research Conference on the European Union     Open Access  
Class, Race and Corporate Power     Open Access   (Followers: 2)
Cold War History     Hybrid Journal   (Followers: 20)
Colección     Open Access  
Commonwealth & Comparative Politics     Hybrid Journal   (Followers: 11)
Communication, Politics & Culture     Open Access   (Followers: 12)
Comparative Cultural Studies : European and Latin American Perspectives     Open Access   (Followers: 5)
Comparative Political Studies     Hybrid Journal   (Followers: 171)
Comparative Politics (Russia)     Open Access   (Followers: 4)
Comparative Strategy     Hybrid Journal   (Followers: 9)
Competition & Change     Hybrid Journal   (Followers: 12)
Complexity, Governance & Networks     Open Access   (Followers: 2)
Confines     Open Access  
Conflict and Society     Open Access   (Followers: 4)
Conflict Management and Peace Science     Hybrid Journal   (Followers: 31)
Conflict, Security & Development     Hybrid Journal   (Followers: 270)
Conflicto Social     Open Access  
Congress & the Presidency: A Journal of Capital Studies     Hybrid Journal   (Followers: 3)
Conhecer : Debate entre o Público e o Privado     Open Access  
Connexe : Questioning Post-Communist Spaces     Open Access  
Constellations     Hybrid Journal   (Followers: 26)
Contemporary Italian Politics     Hybrid Journal   (Followers: 5)
Contemporary Japan     Hybrid Journal   (Followers: 7)
Contemporary Journal of African Studies     Full-text available via subscription   (Followers: 2)
Contemporary Levant     Hybrid Journal  
Contemporary Political Theory     Hybrid Journal   (Followers: 52)
Contemporary Review of the Middle East     Full-text available via subscription   (Followers: 10)
Contemporary Security Policy     Hybrid Journal   (Followers: 18)
Contemporary Southeast Asia: A Journal of International and Strategic Affairs     Full-text available via subscription   (Followers: 18)
Contemporary Wales     Full-text available via subscription   (Followers: 1)
Contenciosa     Open Access  
Cooperation and Conflict     Hybrid Journal   (Followers: 25)
Counterculture Studies     Open Access   (Followers: 1)
Criterios     Open Access  
Critical Asian Studies     Hybrid Journal   (Followers: 14)
Critical Review : A Journal of Politics and Society     Hybrid Journal   (Followers: 23)
Critical Review of International Social and Political Philosophy     Hybrid Journal   (Followers: 20)
Critical Reviews on Latin American Research     Open Access   (Followers: 4)
Critical Social Policy     Hybrid Journal   (Followers: 44)
Critical Studies on Security     Hybrid Journal   (Followers: 3)
Critical Studies on Terrorism     Hybrid Journal   (Followers: 56)
Cuadernos de Coyuntura     Open Access  
Cuadernos de Gibraltar : Gibraltar Reports     Open Access  
Cuadernos de historia de España     Open Access   (Followers: 3)
Cuadernos Latinoamericanos de Administración     Open Access  
Cuestiones Políticas     Open Access  
Cultura de Paz     Open Access  
Cultura Latinoamericana     Open Access   (Followers: 1)
Cultural Critique     Full-text available via subscription   (Followers: 11)
Cultural Logic : A Journal of Marxist Theory & Practice     Open Access   (Followers: 1)
Cywilizacja i Polityka     Open Access  
Data & Policy     Open Access   (Followers: 3)
De Europa     Open Access  
Debater a Europa     Open Access  
Decolonization : Indigeneity, Education & Society     Open Access   (Followers: 14)
Defence Studies     Hybrid Journal   (Followers: 27)
Defense & Security Analysis     Hybrid Journal   (Followers: 26)
Democracy & Education     Open Access   (Followers: 15)
Democratic Communiqué     Open Access   (Followers: 1)
Democratic Theory     Open Access   (Followers: 11)
Democratization     Hybrid Journal   (Followers: 46)
Democrazia e diritto     Full-text available via subscription   (Followers: 2)
Demokratizatsiya: The Journal of Post-Soviet Democratization     Full-text available via subscription   (Followers: 10)
Desafíos     Open Access   (Followers: 1)
Development and Change     Hybrid Journal   (Followers: 58)
Digest of Middle East Studies     Hybrid Journal   (Followers: 13)
Digital Government : Research and Practice     Open Access   (Followers: 1)
Diplomacy & Statecraft     Hybrid Journal   (Followers: 13)
Diplomatic History     Hybrid Journal   (Followers: 24)
Discurso     Open Access  
Dissent     Full-text available via subscription   (Followers: 7)
Diversité urbaine     Full-text available via subscription  
Dynamics of Asymmetric Conflict: Pathways toward terrorism and genocide     Hybrid Journal   (Followers: 12)
Earth System Governance     Open Access   (Followers: 1)
East European Jewish Affairs     Hybrid Journal   (Followers: 17)
East European Politics     Hybrid Journal   (Followers: 16)
East/West : Journal of Ukrainian Studies     Open Access  
Eastern African Literary and Cultural Studies     Hybrid Journal  

        1 2 3 4 5 | Last

Similar Journals
Journal Cover
Data & Policy
Number of Followers: 3  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2632-3249
Published by Cambridge University Press Homepage  [353 journals]
  • International agricultural trade forecasting using machine learning

    • Authors: Gopinath; Munisamy, Batarseh, Feras A., Beckman, Jayson, Kulkarni, Ajay, Jeong, Sei
      First page: 1
      Abstract: Focusing on seven major agricultural commodities with a long history of trade, this study employs data-driven analytics to decipher patterns of trade, namely using supervised machine learning (ML), as well as neural networks. The supervised ML and neural network techniques are trained on data until 2010 and 2014, respectively. Results show the high relevance of ML models to forecasting trade patterns in near- and long-term relative to traditional approaches, which are often subjective assessments or time-series projections. While supervised ML techniques quantified key economic factors underlying agricultural trade flows, neural network approaches provide better fits over the long term.
      PubDate: 2021-01-22
      DOI: 10.1017/dap.2020.22
       
  • A recommendation and risk classification system for connecting rough
           sleepers to essential outreach services

    • Authors: Wilde; Harrison, Chen, Lucia L., Nguyen, Austin, Kimpel, Zoe, Sidgwick, Joshua, De Unanue, Adolfo, Veronese, Davide, Mateen, Bilal, Ghani, Rayid, Vollmer, Sebastian
      First page: 2
      Abstract: Rough sleeping is a chronic experience faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link (HL), a UK-based charity, in developing a data-driven approach to better connect people sleeping rough on the streets with outreach service providers. HL's platform has grown exponentially in recent years, leading to thousands of alerts per day during extreme weather events; this overwhelms the volunteer-based system they currently rely upon for the processing of alerts. In order to solve this problem, we propose a human-centered machine learning system to augment the volunteers' efforts by prioritizing alerts based on the likelihood of making a successful connection with a rough sleeper. This addresses capacity and resource limitations whilst allowing HL to quickly, effectively, and equitably process all of the alerts that they receive. Initial evaluation using historical data shows that our approach increases the rate at which rough sleepers are found following a referral by at least 15% based on labeled data, implying a greater overall increase when the alerts with unknown outcomes are considered, and suggesting the benefit in a trial taking place over a longer period to assess the models in practice. The discussion and modeling process is done with careful considerations of ethics, transparency, and explainability due to the sensitive nature of the data involved and the vulnerability of the people that are affected.
      PubDate: 2021-01-22
      DOI: 10.1017/dap.2020.23
       
  • From satisficing to artificing: The evolution of administrative
           decision-making in the age of the algorithm

    • Authors: Snow; Thea
      First page: 3
      Abstract: Algorithmic decision tools (ADTs) are being introduced into public sector organizations to support more accurate and consistent decision-making. Whether they succeed turns, in large part, on how administrators use these tools. This is one of the first empirical studies to explore how ADTs are being used by Street Level Bureaucrats (SLBs). The author develops an original conceptual framework and uses in-depth interviews to explore whether SLBs are ignoring ADTs (algorithm aversion); deferring to ADTs (automation bias); or using ADTs together with their own judgment (an approach the author calls “artificing”). Interviews reveal that artificing is the most common use-type, followed by aversion, while deference is rare. Five conditions appear to influence how practitioners use ADTs: (a) understanding of the tool (b) perception of human judgment (c) seeing value in the tool (d) being offered opportunities to modify the tool (e) alignment of tool with expectations.
      PubDate: 2021-01-29
      DOI: 10.1017/dap.2020.25
       
  • Fostering trustworthy data sharing: Establishing data foundations in
           practice

    • Authors: Stalla-Bourdillon; Sophie, Carmichael, Laura, Wintour, Alexsis
      First page: 4
      Abstract: Independent data stewardship remains a core component of good data governance practice. Yet, there is a need for more robust independent data stewardship models that are able to oversee data-driven, multi-party data sharing, usage and re-usage, which can better incorporate citizen representation, especially in relation to personal data. We propose that data foundations—inspired by Channel Islands’ foundations laws—provide a workable model for good data governance not only in the Channel Islands, but also elsewhere. A key advantage of this model—in addition to leveraging existing legislation and building on established precedent—is the statutory role of the guardian that is a unique requirement in the Channel Islands, and when interpreted in a data governance model provides the independent data steward. The principal purpose for this paper, therefore, is to demonstrate why data foundations are well suited to the needs of data sharing initiatives. We further examine how data foundations could be established in practice—and provide key design principles that should be used to guide the design and development of any data foundation.
      PubDate: 2021-02-05
      DOI: 10.1017/dap.2020.24
       
  • The value of data matching for public poverty initiatives: a local voucher
           program example

    • Authors: Giest; Sarah, Miotto, Jose M., Kraaij, Wessel
      First page: 5
      Abstract: The recent surge of data-driven methods in social policy have created new opportunities to assess existing poverty programs. The expectation is that the combination of advanced methods and more data can calculate the effectiveness of public interventions more accurately and tailor local initiatives accordingly. Specifically, nonmonetary indicators are increasingly being measured at micro levels in order to target social exclusion in combination with poverty. However, the multidimensional character of poverty, local context, and data matching pose challenges to data-driven analyses. By linking Dutch household-level data with policy-initiative-specific data at local level, we present an explorative study on the uptake of a local poverty pass. The goal is to unravel pass usage in terms of household income and location as well as the age of users. We find that income and age play a role in whether the pass is used, and usage differs per neighborhood. With this, the paper feeds into the discourse on how to operationalize and design data matching work in the multidimensional space of poverty and nonmonetary government initiatives.
      PubDate: 2021-05-18
      DOI: 10.1017/dap.2021.2
       
  • Reimagining data responsibility: 10 new approaches toward a culture of
           trust in re-using data to address critical public needs

    • Authors: Verhulst; Stefaan G.
      First page: 6
      Abstract: Data and data science offer tremendous potential to address some of our most intractable public problems (including the Covid-19 pandemic). At the same time, recent years have shown some of the risks of existing and emerging technologies. An updated framework is required to balance potential and risk, and to ensure that data is used responsibly. Data responsibility is not itself a new concept. However, amid a rapidly changing technology landscape, it has become increasingly clear that the concept may need updating, in order to keep up with new trends such as big data, open data, the Internet of things, and artificial intelligence, and machine learning. This paper seeks to outline 10 approaches and innovations for data responsibility in the 21st century. The 10 emerging concepts we have identified include:End-to-end data responsibilityDecision provenanceProfessionalizing data stewardshipFrom data science to question scienceContextual consentResponsibility by designData asymmetries and data collaborativesPersonally identifiable inferenceGroup privacyData assembliesEach of these is described at greater length in the paper, and illustrated with examples from around the world. Put together, they add up to a framework or outline for policy makers, scholars, and activists who seek to harness the potential of data to solve complex social problems and advance the public good. Needless to say, the 10 approaches outlined here represent just a start. We envision this paper more as an exercise in agenda-setting than a comprehensive survey.
      PubDate: 2021-05-18
      DOI: 10.1017/dap.2021.4
       
  • The contribution of telco data to fight the COVID-19 pandemic: Experience
           of Telefonica throughout its footprint

    • Authors: de Alarcon; Pedro A., Salevsky, Alejandro, Gheti-Kao, Daniel, Rosalen, Willian, Duarte, Marby C., Cuervo, Carlos, Muñoz, Jose J., Pascual, Juan M., Schurig, Martin, Treß, Thomas, Diaz, Elena, de la Cuesta, Carlos, Frias-Martinez, Enrique
      First page: 7
      Abstract: The COVID-19 pandemic is a global challenge for humanity, in which a large number of resources are invested to develop effective vaccines and treatments. At the same time, governments try to manage the spread of the disease while alleviating the strong impact derived from the slowdown in economic activity. Governments were forced to impose strict lockdown measures to tackle the pandemic. This significantly changed people’s mobility and habits, subsequently impacting the economy. In this context, the availability of tools to effectively monitor and quantify mobility was key for public institutions to decide which policies to implement and for how long. Telefonica has promoted different initiatives to offer governments mobility insights throughout many of the countries where it operates in Europe and Latin America. Mobility indicators with high spatial granularity and frequency of updates were successfully deployed in different formats. However, Telefonica faced many challenges (not only technical) to put these tools into service in a short timing: from reducing latency in insights to ensuring the security and privacy of information. In this article, we provide details on how Telefonica engaged with governments and other stakeholders in different countries as a response to the pandemic. We also cover the challenges faced and the shared learnings from Telefonica’s experience in those countries.
      PubDate: 2021-06-28
      DOI: 10.1017/dap.2021.6
       
  • On the use of data from multiple mobile network operators in Europe to
           fight COVID-19

    • Authors: Vespe; Michele, Iacus, Stefano Maria, Santamaria, Carlos, Sermi, Francesco, Spyratos, Spyridon
      First page: 8
      Abstract: The rapid spread of COVID-19 infections on a global level has highlighted the need for accurate, transparent and timely information regarding collective mobility patterns to inform de-escalation strategies as well as to provide forecasting capacity for re-escalation policies aiming at addressing further waves of the virus. Such information can be extracted using aggregate anonymized data from innovative sources such as mobile positioning data. This paper presents lessons learnt and results of a unique Business-to-Government initiative between several mobile network operators in Europe and the European Commission. Mobile positioning data have supported policy-makers and practitioners with evidence and data-driven knowledge to understand and predict the spread of the disease, the effectiveness of the containment measures, their socio-economic impacts while feeding scenarios at European Union scale and in a comparable way across countries. The challenges of these data sharing initiative are not limited to data quality, harmonization, and comparability across countries, however important they are. Equally essential aspects that need to be addressed from the onset are related to data privacy, security, fundamental rights, and commercial sensitivity.
      PubDate: 2021-06-28
      DOI: 10.1017/dap.2021.9
       
  • The hidden potential of call detail records in The Gambia

    • Authors: Arai; Ayumi, Knippenberg, Erwin, Meyer, Moritz, Witayangkurn, Apichon
      First page: 9
      Abstract: Aggregated data from mobile network operators (MNOs) can provide snapshots of population mobility patterns in real time, generating valuable insights when other more traditional data sources are unavailable or out-of-date. The COVID-19 pandemic has highlighted the value of remotely-collected, high-frequency, localized data in inferring the economic impact of shocks to inform decision-making. However, proper protocols must be put in place to ensure end-to-end user-confidentiality and compliance with international best practice. We demonstrate how to build such a data pipeline, channeling data from MNOs through the national regulator to the analytical users, who in turn produce policy-relevant insights. The aggregated indicators analyzed offer a detailed snapshot of the decrease in mobility and increased out-migration from urban to rural areas during the COVID-19 lockdown. Recommendations based on lessons learned from this process can inform engagements with other regulators in creating data pipelines to inform policy-making.
      PubDate: 2021-06-25
      DOI: 10.1017/dap.2021.7
       
  • The French official statistics strategy: Combining signaling data from
           various mobile network operators for documenting COVID-19 crisis effects
           on population movements and economic outlook

    • Authors: Coudin; Elise, Poulhes, Mathilde, Suarez Castillo, Milena
      First page: 10
      Abstract: During the COVID-19 crisis, the French National Institute of Statistics and Economic Studies (INSEE) used aggregated and anonymous counting indicators based on network signaling data of three of the four mobile network operators (MNOs) in France to measure the distribution of population over the territory during and after the lockdown and to enrich the toolbox of high-frequency economic indicators used to follow the economic situation. INSEE’s strategy was to combine information coming from different MNOs together with the national population estimates it usually produces in order to get more reliable statistics and to measure uncertainty. This paper relates and situates this initiative within the long-term methodological collaborations between INSEE and different MNOs, and INSEE, Eurostat, and some other European national statistical institutes (NSIs). These collaborations aim at constructing experimental official statistics on the population present in a given place and at a given time, from mobile phone data (MPD). The COVID-19 initiative has confirmed that more methodological investments are needed to increase relevance of and trust in these data. We suggest this methodological work should be done in close collaboration between NSIs, MNOs, and research, to construct the most reliable statistical processes. This work requires exploiting raw data, so the research and statistical exemptions present in the general data protection regulation (GDPR) should be introduced as well in the new e-privacy regulation. We also raise the challenges of articulating commercial and public interest rationales and articulating transparency and commercial secrets requirements. Finally, it elaborates on the role NSIs can play in the MPD valorization ecosystem.
      PubDate: 2021-06-24
      DOI: 10.1017/dap.2021.1
       
  • Analysis of call detail records to inform the COVID-19 response in
           Ghana—opportunities and challenges

    • Authors: Li; Tracey, Bowers, Rachel, Seidu, Omar, Akoto-Bamfo, Gloria, Bessah, David, Owusu, Victor, Smeets, Laurent
      First page: 11
      Abstract: Telecommunications data are being explored by many countries as a new source of data that can be incorporated into their national statistical systems. In particular, “mobile positioning data” are increasingly being used to study population movements and population distributions. However, the legal, ethical, and technical complexities of working with this type of data often pose many barriers, which can prevent the data from being used at the times when it is most urgently needed. We demonstrate how having a robust public–private partnership framework, a privacy-preserving technical setup, and a communications strategy already in place, prior to an emergency, can enable governments to harness the advantages of telecommunications data at the times when it is most valuable. However, even once these foundations are in place, the challenges of competing priorities, managing expectations, and maintaining communication with data consumers during a pandemic mean that the potential of the data is not automatically translated into direct impact. This highlights the importance of sensitisation exercises, targeted at potential data users, to make clear the potential and limitations of the data, as well as the importance of being able to maintain direct communication with data users. The views expressed in this work belong solely to the authors and should not be interpreted as the views of their institutions.
      PubDate: 2021-06-23
      DOI: 10.1017/dap.2021.5
       
  • The accuracy versus interpretability trade-off in fraud detection model

    • Authors: Nesvijevskaia; Anna, Ouillade, Sophie, Guilmin, Pauline, Zucker, Jean-Daniel
      First page: 12
      Abstract: Like a hydra, fraudsters adapt and circumvent increasingly sophisticated barriers erected by public or private institutions. Among these institutions, banks must quickly take measures to avoid losses while guaranteeing the satisfaction of law-abiding customers. Facing an expanding flow of operations, effective banking relies on data analytics to support established risk control processes, but also on a better understanding of the underlying fraud mechanism. In addition, fraud being a criminal offence, the evidential aspect of the process must also be considered. These legal, operational, and strategic constraints lead to compromises on the means to be implemented for fraud management. This paper first focuses on the translation of practical questions raised in the banking industry at each step of the fraud management process into performance evaluation required to design a fraud detection model. Secondly, it considers a range of machine learning approaches that address these specificities: the imbalance between fraudulent and nonfraudulent operations, the lack of fully trusted labels, the concept-drift phenomenon, and the unavoidable trade-off between accuracy and interpretability of detection. This state-of-the-art review sheds some light on a technology race between black box machine learning models improved by post-hoc interpretation and intrinsic interpretable models boosted to gain accuracy. Finally, it discusses how concrete and promising hybrid approaches can provide pragmatic, short-term answers to banks and policy makers without swallowing up stakeholders with economical and ethical stakes in this technological race.
      PubDate: 2021-07-05
      DOI: 10.1017/dap.2021.3
       
  • Research directions in policy modeling: Insights from comparative analysis
           of recent projects

    • Authors: Ronzhyn; Alexander, Wimmer, Maria A.
      First page: 13
      Abstract: With the increased availability of data and the capacity to make sense of these data, computational approaches to analyze, model and simulate public policy evolved toward viable instruments to deliberate, plan, and evaluate them in different areas of application. Such examples include infrastructure, mobility, monetary, or austerity policies, policies on different aspects of societies (health, pandemic, skills, inclusion, etc.). Technological advances along with the evolution of theoretical models and frameworks open valuable opportunities, while at the same time, posing new challenges. The paper investigates the current state of research in the domain and aims at identifying the most pressing areas for future research. This is done through both literature research of policy modeling and the analysis of research and innovation projects that either focus on policy modeling or involve it as a significant component of the research design. In the paper, 16 recent projects involving the keyword policy modeling were analyzed. The majority of projects concern the application of policy modeling to a specific domain or area of interest, while several projects tackled the cross-cutting topics (risk and crisis management). The detailed analysis of the projects led to topics of future research in the domain of policy modeling. Most prominent future research topics in policy modeling include stakeholder involvement approaches, applicability of research results, handling complexity of models, integration of models from different modeling and simulation paradigms and approaches, visualization of simulation results, real-time data processing, and scalability. These aspects require further research to appropriately contribute to further advance the field.
      PubDate: 2021-07-13
      DOI: 10.1017/dap.2021.8
       
  • How data governance technologies can democratize data sharing for
           community well-being

    • Authors: Wu; Dan, Verhulst, Stefaan, Pentland, Alex, Avila, Thiago, Finch, Kelsey, Gupta, Abhishek
      First page: 14
      Abstract: Data sharing efforts to allow underserved groups and organizations to overcome the concentration of power in our data landscape. A few special organizations, due to their data monopolies and resources, are able to decide which problems to solve and how to solve them. But even though data sharing creates a counterbalancing democratizing force, it must nevertheless be approached cautiously. Underserved organizations and groups must navigate difficult barriers related to technological complexity and legal risk. To examine what those common barriers are, one type of data sharing effort—data trusts—are examined, specifically the reports commenting on that effort. To address these practical issues, data governance technologies have a large role to play in democratizing data trusts safely and in a trustworthy manner. Yet technology is far from a silver bullet. It is dangerous to rely upon it. But technology that is no-code, flexible, and secure can help more responsibly operate data trusts. This type of technology helps innovators put relationships at the center of their efforts.
      PubDate: 2021-07-13
      DOI: 10.1017/dap.2021.13
       
  • Rethinking digital identity for post-COVID-19 societies: Data privacy and
           human rights considerations

    • Authors: Beduschi; Ana
      First page: 15
      Abstract: The COVID-19 pandemic has exposed the need for more contactless interactions, leading to an acceleration in the design, development, and deployment of digital identity tools and contact-free solutions. A potentially positive outcome of the current crisis could be the development of a more data privacy and human rights compliant framework for digital identity. However, for such a framework to thrive, two essential conditions must be met: (1) respect for and protection of data privacy irrespective of the type of architecture or technology chosen and (2) consideration of the broader impacts that digital identity can have on individuals’ human rights. The article draws on legal, technology-facing, and policy-oriented academic literature to evaluate each of these conditions. It then proposes two ways to leverage the process of digitalization strengthened by the pandemic: a data privacy-centric and a human rights-based approach to digital identity solutions fit for post-COVID-19 societies.
      PubDate: 2021-07-14
      DOI: 10.1017/dap.2021.15
       
  • Exploring city digital twins as policy tools: A task-based approach to
           generating synthetic data on urban mobility

    • Authors: Papyshev; Gleb, Yarime, Masaru
      First page: 16
      Abstract: This article discusses the technology of city digital twins (CDTs) and its potential applications in the policymaking context. The article analyzes the history of the development of the concept of digital twins and how it is now being adopted on a city-scale. One of the most advanced projects in the field—Virtual Singapore—is discussed in detail to determine the scope of its potential domains of application and highlight challenges associated with it. Concerns related to data privacy, availability, and its applicability for predictive simulations are analyzed, and potential usage of synthetic data is proposed as a way to address these challenges. The authors argue that despite the abundance of urban data, the historical data are not always applicable for predictions about the events for which there does not exist any data, as well as discuss the potential privacy challenges of the usage of micro-level individual mobility data in CDTs. A task-based approach to urban mobility data generation is proposed in the last section of the article. This approach suggests that city authorities can establish services responsible for asking people to conduct certain activities in an urban environment in order to create data for possible policy interventions for which there does not exist useful historical data. This approach can help in addressing the challenges associated with the availability of data without raising privacy concerns, as the data generated through this approach will not represent any real individual in society.
      PubDate: 2021-07-16
      DOI: 10.1017/dap.2021.17
       
  • The use of anonymized and aggregated telecom mobility data by a public
           health agency during the COVID-19 pandemic: Learnings from both the
           operator and agency perspective

    • Authors: Ågren; Kristofer, Bjelkmar, Pär, Allison, Elin
      First page: 17
      Abstract: The COVID-19 pandemic and associated measures implemented have rapidly changed how people move about and behave in society. Utilizing data on people’s mobility could provide unique and valuable insights to governments and institutions to better manage the crisis. These entities, however, have not traditionally had access to, nor the experience of applying, continuous anonymized and aggregated data on people mobility. This article aims to show how the Public Health Agency in Sweden successfully collaborated with a Nordic Telecoms operator to make use of such data during the COVID-19 pandemic. Specifically, it investigates how the collaboration started, approaches used to go from data to insight, outcomes and impact, and lessons learned on both sides. Telia, the largest telecom operator in the Nordics, had an existing product commercially available that provided anonymized and aggregated insights about people’s movement. Several challenges existed within Telia as it was the first time worldwide a collaboration with a Public Health Agency would take place and social benefits had to be weighed against commercial and reputational risks. The hypothesis at the beginning of the pandemic was that the solution could be adapted to fit the needs of policymakers and the internal challenges could be overcome, while providing a meaningful contribution to the fight against the virus. The results show that it is possible to both form a mutually beneficial collaboration between a telecom operator and a public institution, and to make use of mobility data in evidence-based policymaking without compromising applicable personal data protection laws.
      PubDate: 2021-08-09
      DOI: 10.1017/dap.2021.11
       
  • Understanding migrants in COVID-19 counting: Rethinking the
           data-(in)visibility nexus

    • Authors: Pelizza; Annalisa, Milan, Stefania, Lausberg, Yoren
      First page: 18
      Abstract: The COVID-19 pandemic confronts society with a dilemma between (in)visibility, security, and care. While invisibility might be sought by unregistered and undocumented people, being counted and thus visible during a pandemic is a precondition of existence and care. This article asks whether and how unregistered populations like undocumented migrants should be included in statistics and other “counting” exercises devised to track virus diffusion and its impact. In particular, the paper explores how such inclusion can be just, given that for unregistered people visibility is often associated with surveillance. It also reflects on how policymaking can act upon the relationship between data, visibility, and populations in pragmatic terms. Conversing with science and technology studies and critical data studies, the paper frames the dilemma between (in)visibility and care as an issue of sociotechnical nature and identifies four criteria linked to the sociotechnical characteristics of the data infrastructure enabling visibility. It surveys “counting” initiatives targeting unregistered and undocumented populations undertaken by European countries in the aftermath of the pandemic, and illustrates the medical, economic, and social consequences of invisibility. On the basis of our analysis, we outline four scenarios that articulate the visibility/invisibility binary in novel, nuanced terms, and identify in the “de facto inclusion” scenario the best option for both migrants and the surrounding communities. Finally, we offer policy recommendations to avoid surveillance and overreach and promote instead a more just “de facto” civil inclusion of undocumented populations.
      PubDate: 2021-08-20
      DOI: 10.1017/dap.2021.19
       
  • Using mobile phone data for epidemic response in low resource settings—A
           case study of COVID-19 in Malawi

    • Authors: Green; Dylan, Moszczynski, Michael, Asbah, Samer, Morgan, Cassie, Klyn, Brandon, Foutry, Guillaume, Ndira, Simon, Selman, Noah, Monawe, Maganizo, Likaka, Andrew, Sibande, Rachel, Smith, Tyler
      First page: 19
      Abstract: The COVID-19 global pandemic has had considerable health impact, including sub-Saharan Africa. In Malawi, a resource-limited setting in Africa, gaining access to data to inform the COVID-19 response is challenging. Information on adherence to physical distancing guidelines and reducing contacts are nonexistent, but critical to understanding and communicating risk, as well as allocating scarce resources. We present a case study which leverages aggregated call detail records into a daily data pipeline which summarize population density and mobility in an easy-to-use dashboard for public health officials and emergency operations. From March to April 2021, we have aggregated 6-billion calls and text messages and continue to process 12 million more daily. These data are summarized into reports which describe, quantify, and locate mass gatherings and travel between subdistricts. These reports are accessible via web dashboards for policymakers within the Ministry of Health and Emergency Operations Center to inform COVID-19 response efforts and resource allocation.
      PubDate: 2021-08-09
      DOI: 10.1017/dap.2021.14
       
  • Challenges and opportunities in accessing mobile phone data for COVID-19
           response in developing countries

    • Authors: Milusheva; Sveta, Lewin, Anat, Begazo Gomez, Tania, Matekenya, Dunstan, Reid, Kyla
      First page: 20
      Abstract: Anonymous and aggregated statistics derived from mobile phone data have proven efficacy as a proxy for human mobility in international development work and as inputs to epidemiological modeling of the spread of infectious diseases such as COVID-19. Despite the widely accepted promise of such data for better development outcomes, challenges persist in their systematic use across countries. This is not only the case for steady-state development use cases such as in the transport or urban development sectors, but also for sudden-onset emergencies such as epidemics in the health sector or natural disasters in the environment sector. This article documents an effort to gain systematized access to and use of anonymized, aggregated mobile phone data across 41 countries, leading to fruitful collaborations in nine developing countries over the course of one year. The research identifies recurring roadblocks and replicable successes, offers lessons learned, and calls for a bold vision for future successes. An emerging model for a future that enables steady-state access to insights derived from mobile big data - such that they are available over time for development use cases - will require investments in coalition building across multiple stakeholders, including local researchers and organizations, awareness raising of various key players, demand generation and capacity building, creation and adoption of standards to facilitate access to data and their ethical use, an enabling regulatory environment and long-term financing schemes to fund these activities.
      PubDate: 2021-09-15
      DOI: 10.1017/dap.2021.10
       
  • Using mobile big data to support emergency preparedness and address
           economically vulnerable communities during the COVID-19 pandemic in
           Nigeria

    • Authors: Gilbert; Joanne, Adekanmbi, Olubayo, Harrison, Charlie
      First page: 21
      Abstract: With the declaration of the coronavirus disease 2019 (COVID-19) pandemic in Nigeria in 2020, the Nigeria Governors’ Forum (NGF) instigated a collaboration with MTN Nigeria to develop data-driven insights, using mobile big data (MBD) and other data sources, to shape the planning and response to the pandemic. First, a model was developed to predict the worst-case scenario for infections in each state. This was used to support state-level health committees to make local resource planning decisions. Next, as containment interventions resulted in subsistence/daily paid workers losing their income and ability to buy essential food supplies, NGF and MTN agreed a second phase of activity, to develop insights to understand the population clusters at greatest socioeconomic risk from the impact of the pandemic. This insight was used to promote available financial relief to the economically vulnerable population clusters in Lagos state via the HelpNow crowdfunding initiative. This article discusses how anonymized and aggregated mobile network data (MBD), combined with other data sources, were used to create valuable insights and inform the government, and private business, response to the pandemic in Nigeria. Finally, we discuss lessons learnt. Firstly, how a collaboration with, and support from, the regulator enabled MTN to deliver critical insights at a national scale. Secondly, how the Nigeria Data Protection Regulation and the GSMA COVID-19 Privacy Guidelines provided an initial framework to open the discussion and define the approach. Thirdly, why stakeholder management is critical to the understanding, and application, of insights. Fourthly, how existing relationships ease new project collaborations. Finally, how MTN is developing future preparedness by creating a team that is focused on developing data-driven insights for social good.
      PubDate: 2021-09-15
      DOI: 10.1017/dap.2021.12
       
  • Using Vodafone mobile phone network data to provide insights into citizens
           mobility in Italy during the Coronavirus outbreak

    • Authors: Calabrese; Francesco, Cobelli, Enrico, Ferraiuolo, Vincenzo, Misseri, Giovanni, Pinelli, Fabio, Rodriguez, Daniel
      First page: 22
      Abstract: In this paper, we present the work conducted by Vodafone to enrich the understanding of people movement in Italy during the outbreak of the Coronavirus in 2020, and the tool developed to support the decisions taken by the authorities during that period. We have developed a solution to anonymously monitor the daily movements of Vodafone SIMs in Italy, at aggregate level, at different spatial and temporal granularity, to provide insights into the movements of Italians.
      PubDate: 2021-09-15
      DOI: 10.1017/dap.2021.18
       
  • How data governance technologies can democratize data sharing for
           community well-being – Corrigendum

    • Authors: Wu; Dan, Verhulst, Stefaan G., Pentland, Alex, Avila, Thiago, Finch, Kelsey, Gupta, Abhishek
      First page: 23
      PubDate: 2021-09-24
      DOI: 10.1017/dap.2021.22
       
  • Guiding principles to maintain public trust in the use of mobile operator
           data for policy purposes

    • Authors: Jansen; Ronald, Kovacs, Karoly, Esko, Siim, Saluveer, Erki, Sõstra, Kaja, Bengtsson, Linus, Li, Tracey, Adewole, Wole A., Nester, Jade, Arai, Ayumi, Magpantay, Esperanza
      First page: 24
      Abstract: The COVID-19 pandemic has accelerated the use of mobile operator data to support public policy, although without a universal governance framework for its application. This article describes five principles to guide and assist statistical agencies, mobile network operators and intermediary service providers, who are actively working on projects using mobile operator data to support governments in monitoring the effectiveness of its COVID-19 related interventions. These are principles of necessity and proportionality, of professional independence, of privacy protection, of commitment to quality, and of international comparability. Compliance with each of these principles can help maintain public trust in the handling of these sensitive data and their results, and therefore keep citizen support for government policies. Three projects (in Estonia, Ghana, and the Gambia) were described and reviewed with respect to the compliance and applicability of the five principles. Most attention was placed on privacy protection, somewhat at the expense of the quality of the compiled indicators. The necessity and proportionality in the choice of mobile operator data can be very well justified given the need for timely, frequent and granular indicators. Explicitly addressing the five principles in the preparation of a project should give confidence to the statistical agency and its partners, that enough care has been exercised in the set up and implementation of the project, and should convey trust to public and government in the use mobile operator data for policy purposes.
      PubDate: 2021-10-01
      DOI: 10.1017/dap.2021.21
       
  • IoT innovation clusters in Europe and the case for public policy

    • Authors: Remotti; Luca Alessandro
      First page: 25
      Abstract: The Internet of Things (IoT) is currently developing fast and its potential as driver of innovative solutions is increasing, pushed by technologies, networks, communication, and computing power, and has the potential to drive the development of technological ecosystems, such as innovation clusters. Innovation clusters are agglomeration of enterprises and research organizations, which cooperate, interact and compete, generating innovation and driving the growth of ecosystems. The narrative around innovation clusters has been developing since many years and policy-makers seek to use such clusters as a policy instrument to support the growth of technology on the one hand and regional and sectoral development on the other hand. This policy paper expands an empirical study on IoT innovation clusters in Europe and places it within the current debate around clusters and innovation clusters to provide evidence-based advice to policy-makers on what may and may not work as public policy measures. The paper highlights the findings of the interaction with several hundred European IoT innovation clusters and points out their points of view on their own creation factors, operational characteristics, and success stories, as well as their expectations in respect to policy interventions for IoT and for clusters. Suggestions for IoT policy-making are provided. The paper has also undertaken an extensive review of up-to date research on innovation cluster creation and performance, thoroughly analyzing the real possibility to define causal relationships between clusters, productivity and economic growth, and business performance, and providing suggestions for policy-makers on the approach to cluster policy.
      PubDate: 2021-10-11
      DOI: 10.1017/dap.2021.16
       
  • Decision support system for flood risk reduction policies: The case of a
           flood protection measure in the area of Vicenza

    • Authors: Pantalona; Georgia, Tsalakanidou, Filareti, Nikolopoulos, Spiros, Kompatsiaris, Ioannis, Lombardo, Francesca, Norbiato, Daniele, Ferri, Michele, Kovats, Laszlo, Haberstock, Holger
      First page: 26
      Abstract: Climate change is one of the most significant and pressing issues faced by humanity; it frequently results in major natural disasters, such as catastrophic floods, which require the establishment of effective management policies by local and national authorities. These policies involve complex multistep decision-making processes that require combined assessment of various sources of data by different stakeholders. Even though an abundance of data is being collected to monitor climate change and estimate its consequences on the society, the environment, and the economy, policy-making is still largely based on intuition rather than evidence due to lack of a structured approach for modeling the decision-making process and considering the appropriate use of data in every step of the process. The goal of this work is to introduce a novel decision support system that can guide policy makers through a structured data-driven decision-making process aiming to create policies for flood risk management. The proposed system is a multifacet platform that guides policy makers through five phases—inform, advise, monitor, evaluate, and revise—of the policy cycle. For each phase, different dashboards provide relevant information regarding the environmental, social, and economic conditions. To demonstrate the potential of the proposed system, we use it to assess a flood protection policy in the city of Vicenza, Italy. The results reveal the benefits and challenges of the proposed decision support tool for public administrations involved in flood risk management.
      PubDate: 2021-10-22
      DOI: 10.1017/dap.2021.23
       
  • Evaluating the trade-off between privacy, public health safety, and
           digital security in a pandemic

    • Authors: Akinsanmi; Titi, Salami, Aishat
      First page: 27
      Abstract: COVID-19 has impacted all aspects of everyday normalcy globally. During the height of the pandemic, people shared their (PI) with one goal—to protect themselves from contracting an “unknown and rapidly mutating” virus. The technologies (from applications based on mobile devices to online platforms) collect (with or without informed consent) large amounts of PI including location, travel, and personal health information. These were deployed to monitor, track, and control the spread of the virus. However, many of these measures encouraged the trade-off on privacy for safety. In this paper, we reexamine the nature of privacy through the lens of safety focused on the health sector, digital security, and what constitutes an infraction or otherwise of the privacy rights of individuals in a pandemic as experienced in the past 18 months. This paper makes a case for maintaining a balance between the benefit, which the contact tracing apps offer in the containment of COVID-19 with the need to ensure end-user privacy and data security. Specifically, it strengthens the case for designing with transparency and accountability measures and safeguards in place as critical to protecting the privacy and digital security of users—in the use, collection, and retention of user data. We recommend oversight measures to ensure compliance with the principles of lawful processing, knowing that these, among others, would ensure the integration of privacy by design principles even in unforeseen crises like an ongoing pandemic; entrench public trust and acceptance, and protect the digital security of people.
      PubDate: 2021-10-28
      DOI: 10.1017/dap.2021.24
       
  • Impact of data accuracy on the evaluation of COVID-19 mitigation policies

    • Authors: Starnini; Michele, Aleta, Alberto, Tizzoni, Michele, Moreno, Yamir
      First page: 28
      Abstract: Evaluating the effectiveness of nonpharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic is crucial to maximize the epidemic containment while minimizing the social and economic impact of these measures. However, this endeavor crucially relies on surveillance data publicly released by health authorities that can hide several limitations. In this article, we quantify the impact of inaccurate data on the estimation of the time-varying reproduction number , a pivotal quantity to gauge the variation of the transmissibility originated by the implementation of different NPIs. We focus on Italy and Spain, two European countries among the most severely hit by the COVID-19 pandemic. For these two countries, we highlight several biases of case-based surveillance data and temporal and spatial limitations in the data regarding the implementation of NPIs. We also demonstrate that a nonbiased estimation of could have had direct consequences on the decisions taken by the Spanish and Italian governments during the first wave of the pandemic. Our study shows that extreme care should be taken when evaluating intervention policies through publicly available epidemiological data and call for an improvement in the process of COVID-19 data collection, management, storage, and release. Better data policies will allow a more precise evaluation of the effects of containment measures, empowering public health authorities to take more informed decisions.
      PubDate: 2021-10-28
      DOI: 10.1017/dap.2021.25
       
  • Increasing resilience via the use of personal data: Lessons from COVID-19
           dashboards on data governance for the public good

    • Authors: Li; Veronica Qin Ting, Yarime, Masaru
      First page: 29
      Abstract: Contemporary data tools such as online dashboards have been instrumental in monitoring the spread of the COVID-19 pandemic. These real-time interactive platforms allow citizens to understand the local, regional, and global spread of COVID-19 in a consolidated and intuitive manner. Despite this, little research has been conducted on how citizens respond to the data on the dashboards in terms of the pandemic and data governance issues such as privacy. In this paper, we seek to answer the research question: how can governments use data tools, such as dashboards, to balance the trade-offs between safeguarding public health and protecting data privacy during a public health crisis' This study used surveys and semi-structured interviews to understand the perspectives of the developers and users of COVID-19 dashboards in Hong Kong. A typology was also developed to assess how Hong Kong’s dashboards navigated trade-offs between data disclosure and privacy at a time of crisis compared to dashboards in other jurisdictions. Results reveal that two key factors were present in the design and improvement of COVID-19 dashboards in Hong Kong: informed actions based on open COVID-19 case data, and significant public trust built on data transparency. Finally, this study argues that norms surrounding reporting on COVID-19 cases, as well as cases for future pandemics, should be co-constructed among citizens and governments so that policies founded on such norms can be acknowledged as salient, credible, and legitimate.
      PubDate: 2021-11-12
      DOI: 10.1017/dap.2021.27
       
  • Measuring outcomes in healthcare economics using Artificial Intelligence:
           With application to resource management

    • Authors: Huang; Chih-Hao, Batarseh, Feras A., Boueiz, Adel, Kulkarni, Ajay, Su, Po-Hsuan, Aman, Jahan
      First page: 30
      Abstract: The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e., Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision-making, as well as in multiple medical and economic aspects at a hospital. External (geographic) or internal factors (medical and managerial) lead to shifts in planning and budgeting, but most importantly, reduce confidence in conventional processes. In some cases, support from other hospitals proves necessary, which exacerbates the planning aspect. This paper presents three data-driven methods that provide data-driven indicators to help healthcare managers organize their economics and identify the most optimum plan for resources allocation and sharing. Conventional decision-making methods fall short in recommending validated policies for managers. Using reinforcement learning, genetic algorithms, traveling salesman, and clustering, we experimented with different healthcare variables and presented tools and outcomes that could be applied at health institutes. Experiments are performed; the results are recorded, evaluated, and presented.
      PubDate: 2021-11-12
      DOI: 10.1017/dap.2021.29
       
  • Knowledge politics in the smart city: A case study of strategic urban
           planning in Cambridge, UK

    • Authors: Nochta; Timea, Wahby, Noura, Schooling, Jennifer M.
      First page: 31
      Abstract: This paper highlights the need and opportunities for constructively combining different types of (analogue and data-driven) knowledges in evidence-informed policy decision-making in future smart cities. Problematizing the assumed universality and objectivity of data-driven knowledge, we call attention to notions of “positionality” and “situatedness” in knowledge production relating to the urban present and possible futures. In order to illustrate our arguments, we draw on a case study of strategic urban (spatial) planning in the Cambridge city region in the United Kingdom. Tracing diverse knowledge production processes, including top-down data-driven knowledges derived from urban modeling, and bottom-up analogue community-based knowledges, allows us to identify locationally specific knowledge politics around evidence for policy. The findings highlight how evidence-informed urban policy can benefit from political processes of competition, contestation, negotiation, and complementarity that arise from interactions between diverse “digital” and “analogue” knowledges. We argue that studying such processes can help in assembling a more multifaceted, diverse and inclusive knowledge-base on which to base policy decisions, as well as to raise awareness and improve active participation in the ongoing “smartification” of cities.
      PubDate: 2021-11-17
      DOI: 10.1017/dap.2021.28
       
  • The role of artificial intelligence in disinformation

    • Authors: Bontridder; Noémi, Poullet, Yves
      First page: 32
      Abstract: Artificial intelligence (AI) systems are playing an overarching role in the disinformation phenomenon our world is currently facing. Such systems boost the problem not only by increasing opportunities to create realistic AI-generated fake content, but also, and essentially, by facilitating the dissemination of disinformation to a targeted audience and at scale by malicious stakeholders. This situation entails multiple ethical and human rights concerns, in particular regarding human dignity, autonomy, democracy, and peace. In reaction, other AI systems are developed to detect and moderate disinformation online. Such systems do not escape from ethical and human rights concerns either, especially regarding freedom of expression and information. Having originally started with ascending co-regulation, the European Union (EU) is now heading toward descending co-regulation of the phenomenon. In particular, the Digital Services Act proposal provides for transparency obligations and external audit for very large online platforms’ recommender systems and content moderation. While with this proposal, the Commission focusses on the regulation of content considered as problematic, the EU Parliament and the EU Council call for enhancing access to trustworthy content. In light of our study, we stress that the disinformation problem is mainly caused by the business model of the web that is based on advertising revenues, and that adapting this model would reduce the problem considerably. We also observe that while AI systems are inappropriate to moderate disinformation content online, and even to detect such content, they may be more appropriate to counter the manipulation of the digital ecosystem.
      PubDate: 2021-11-25
      DOI: 10.1017/dap.2021.20
       
  • Data sharing and collaborations with Telco data during the COVID-19
           pandemic: A Vodafone case study

    • Authors: Lourenco; Pedro Rente, Kaur, Gurjeet, Allison, Matthew, Evetts, Terry
      First page: 33
      Abstract: With the outbreak of COVID-19 across Europe, anonymized telecommunications data provides a key insight into population level mobility and assessing the impact and effectiveness of containment measures. Vodafone’s response across its global footprint was fast and delivered key new metrics for the pandemic that have proven to be useful for a number of external entities. Cooperation with national governments and supra-national entities to help fight the COVID-19 pandemic was a key part of Vodafone’s response, and in this article the different methodologies developed are analyzed, as well as the key collaborations established in this context. In this article we also analyze the regulatory challenges found, and how these can pose a risk of the full benefits of these insights not being harnessed, despite clear and efficient Privacy and Ethics assessments to ensure individual safety and data privacy.
      PubDate: 2021-10-22
      DOI: 10.1017/dap.2021.26
       
  • Data linkage for early intervention in the UK: Parental social license and
           social divisions

    • Authors: Edwards; Rosalind, Gillies, Val, Gorin, Sarah
      First page: 34
      Abstract: Electronic linking of public records and predictive analytics to identify families for preventive early intervention increasingly is promoted by governments. We use the concept of social license to address questions of social legitimacy, agreement, and trust in data linkage and analytics for parents of dependent children, who are the focus of early intervention initiatives in the UK. We review data-steered family policy and early intervention operational service practices. We draw on a consensus baseline analysis of data from a probability-based panel survey of parents, to show that informed consent to data linkage and use is important to all parents, but there are social divisions of knowledge, agreement, and trust. There is more social license for data linkage by services among parents in higher occupation, qualification, and income groups, than among Black parents, lone parents, younger parents, and parents in larger households. These marginalized groups of parents, collectively, are more likely to be the focus of identification for early intervention. We argue that government awareness-raising exercises about the merits of data linkage are likely to bolster existing social license among advantaged parents while running the risk of further disengagement among disadvantaged groups. This is especially where inequalities and forecasting inaccuracies are encoded into early intervention data gathering, linking, and predictive practices, with consequences for a cohesive and equal society.
      PubDate: 2021-12-07
      DOI: 10.1017/dap.2021.34
       
  • Responsible innovation for digital identity systems

    • Authors: Anand; Nishant, Brass, Irina
      First page: 35
      Abstract: Digital identity (eID) systems are a crucial piece in the digital services ecosystem. They connect individuals to a variety of socioeconomic opportunities but can also reinforce power asymmetries between organizations and individuals. Data collection practices can negatively impact an individual’s right to privacy, autonomy, and self-determination. Protecting individual rights, however, may be at odds with imperatives of profit maximization or national security. The use of eID technologies is hence highly contested. Current approaches to governing eID systems have been unable to fully address the trade-offs between the opportunities and risks associated with these systems. The responsible innovation (RI) literature provides a set of principles to govern disruptive innovations, such as eID systems, toward societally desirable outcomes. This article uses RI principles to develop a framework to govern eID systems in a more inclusive, responsible, and user-centered manner. The proposed framework seeks to complement existing practices for eID system governance by bringing forth principles of deliberation and democratic engagement to build trust amongst stakeholders of the eID system and deliver shared socioeconomic benefits.
      PubDate: 2021-12-20
      DOI: 10.1017/dap.2021.35
       
 
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