Desafios na interação digital dos cidadãos com o Estado: uma escala para medir os obstáculos administrativos

Autores

Palavras-chave:

auxílio emergencial, análise fatorial, measurement invariance, obstáculos administrativos

Resumo

Em sua interação com o Estado, os cidadãos frequentemente enfrentam desafios como formulários de elegibilidade, requisitos e regras sem sentido. Estes encargos podem impedir o acesso aos benefícios públicos, particularmente para os pobres, que são vistos como desmerecedores e têm pouco capital social ou humano. Alguns argumentos defendem aplicativos e websites móveis para facilitar o acesso de determinados grupos sociais, mas a tecnologia também pode trazer novos desafios para eles como altos custos, ameaças à privacidade e custos de tempo/emocionais. Este artigo procura desenvolver uma nova escala para medir os encargos administrativos para os cidadãos que se candidatam a benefícios sociais através da interação digital com o Estado. Uma amostra de 413 entrevistados foi utilizada através de grupos do Facebook dedicados a discutir o Auxílio emergencial brasileiro. Os resultados mostraram uma escala com forte confiabilidade e validade, apesar de haver limitações que precisam ser endereçadas em pesquisas futuras.

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Biografia do Autor

Maiara Marinho, Fundação Getúlio Vargas

PhD candidate, Brazilian School of Public and Business Administration (EBAPE/Fundação Getúlio
Vargas). Master in Administration, Universidade Federal Fluminense (UFF). Collaborating Professor at
Getúlio Vargas Foundation (FGV).

Referências

Aarøe, L., Baekgaard, M., Christensen, J., & Moynihan, D. P. (2021). Personality and Public Administration: Policymaker Tolerance of Administrative Burdens in Welfare Services. Public Administration Review, 81(4), 652–663. https://doi.org/10.1111/puar.13381

Alon-Barkat, S., & Busuioc, M. (2021). Decision-makers’ Processing of AI Algorithmic Advice: ‘Automation Bias’ versus Selective Adherence. Journal of Public Administration Research and Theory, 1-17. https://doi.org/10.1093/jopart/muac007

Androutsopoulou, A., Karacapilidis, N., Loukis, E., & Charalabidis, Y. (2019). Transforming the communication between citizens and government through AI-guided chatbots. Government Information Quarterly, 36(2), 358–367. https://doi.org/10.1016/j.giq.2018.10.001

Baekgaard, M., Moynihan, D. P., & Thomsen, M. K. (2021). Why Do Policymakers Support Administrative Burdens? The Roles of Deservingness, Political Ideology, and Personal Experience. Journal of Public Administration Research and Theory, 31(1), 184–200. https://doi.org/10.1093/jopart/muaa033

Bell, E., Ter‐Mkrtchyan, A., Wehde, W., & Smith, K. (2021). Just or Unjust? How Ideological Beliefs Shape Street‐Level Bureaucrats’ Perceptions of Administrative Burden. Public Administration Review, 81(4), 610–624. https://doi.org/10.1111/puar.13311

Binns, R. (2018). Fairness in Machine Learning: Lessons from Political Philosophy. Proceedings of Machine Learning Research. Proceedings of Machine Learning Research, 81, 1–11. https://doi.org/10.48550/arXiv.1712.03586

Boas, T. C., Christenson, D. P., & Glick, D. M. (2020). Recruiting large online samples in the United States and India: Facebook, Mechanical Turk, and Qualtrics. Political Science Research and Methods, 8(2), 232–250. https://doi.org/10.1017/psrm.2018.28

Bovens, M., & Zouridis, S. (2002). From Street‐Level to System‐Level Bureaucracies: How Information and Communication Technology is Transforming Administrative Discretion and Constitutional Control. Public Administration Review, 62(2), 174–184. https://doi.org/10.1111/0033-3352.00168

Bozeman, B., & Youtie, J. (2020). Robotic Bureaucracy: Administrative Burden and Red Tape in University Research. Public Administration Review, 80(1), 157–162. https://doi.org/10.1111/puar.13105

Brasil. (2020, August 21). Auxílio Emergencial chega a 60% da população brasileira. Governo do Brasil. https://www.gov.br/pt-br/noticias/financas-impostos-e-gestao-publica/600-dias/arquivos-de-600-dias/cidadania-auxilio-emergencial-chega-a-60-da-populacao-brasileira

Brodkin, E. Z., & Majmundar, M. (2010). Administrative Exclusion: Organizations and the Hidden Costs of Welfare Claiming. Journal of Public Administration Research and Theory, 20(4), 827–848. https://doi.org/10.1093/jopart/mup046

Buffat, A. (2015). Street-Level Bureaucracy and E-Government. Public Management Review, 17(1), 149–161. https://doi.org/10.1080/14719037.2013.771699

Bullock, J., Young, M. M., & Wang, Y.-F. (2020). Artificial intelligence, bureaucratic form, and discretion in public service. Information Polity, 25(4), 491–506. https://doi.org/10.3233/IP-200223

Cardoso, B. B. (2020). The Implementation of Emergency Aid as an exceptional measure of social protection. Revista de Administração Pública, 54(4), 1052–1063. https://doi.org/10.1590/0034-761220200267x

Carney, T. (2020). Automation in social security: Implications for merits review? Australian Journal of Social Issues, 55(3), 260–274. https://doi.org/10.1002/ajs4.95

Castelluccia, C., & Le Métayer, D. (2019). Understanding algorithmic decision-making: Opportunities and challenges. (European Parliament. Directorate General for Parliamentary Research Services., Ed.). European Union. https://data.europa.eu/doi/10.2861/536131

Chen, F. F. (2007). Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464–504. https://doi.org/10.1080/10705510701301834

Christensen, J., Aarøe, L., Baekgaard, M., Herd, P., & Moynihan, D. P. (2020). Human Capital and administrative burden: The role of cognitive resources in citizen-state interactions. Public Administration Review, 80(1), 127–136. https://doi.org/10.1111/puar.13134

DeVellis, R. F. (2016). Scale development: Theory and applications (Fourth Edition). Sage Publications.

El Akremi, A., Gond, J.-P., Swaen, V., De Roeck, K., & Igalens, J. (2015). How Do Employees Perceive Corporate Responsibility? Development and Validation of a Multidimensional Corporate Stakeholder Responsibility Scale. Journal of Management, 44(2), 619–657. https://doi.org/10.1177/0149206315569311

Eubanks, V. (2018). Automating inequality: How High-Tech Tools Profile, Police, and Punish the Poor (1st ed.). St Martin’s Press.

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

George, D., & Mallery, P. (1998). SPSS for Windows Step by Step (world). https://dl.acm.org/doi/abs/10.5555/551591

Hattke, F. (2019). When the Red Tape Becomes Policy: A Critical Assessment of Administrative Burdens. Journal of Public Administration Research and Theory, 30(1), 178–180. https://doi.org/10.1093/jopart/muz025

Heinrich, C. J. (2016). The Bite of Administrative Burden: A Theoretical and Empirical Investigation. Journal of Public Administration Research and Theory, 26(3), 403–420. https://doi.org/10.1093/jopart/muv034

Herd, P., Harvey, H., DeLeire, T., & Moynihan, D. P. (2013). Shifting Administrative Burden to the State: A Case Study of Medicaid Take-Up. Public Administration Review, 73(S1), 69–81. https://doi.org/10.1111/puar.12114

Herd, P., & Moynihan, D. P. (2018). Administrative Burden: Policymaking by Other Means (1 edition). Russell Sage Foundation.

Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018). Human decisions and machine predictions. The Quarterly Journal of Economics, 133(1), 237–293. https://doi.org/10.1093/qje/qjx032

Larsson, K. K. (2021). Digitization or equality: When government automation covers some, but not all citizens. Government Information Quarterly, 38(1), 101547. https://doi.org/10.1016/j.giq.2020.101547

Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 205395171875668. https://doi.org/10.1177/2053951718756684

Mansur, J., Sobral, F., & Goldszmidt, R. (2017). Shades of paternalistic leadership across cultures. Journal of World Business, 52(5), 702–713. https://doi.org/10.1016/j.jwb.2017.06.003

Masood, A., & Nisar, M. A. (2021). Administrative Capital and Citizens’ Responses to Administrative Burden. Journal of Public Administration Research and Theory, 31(1), 56–72. https://doi.org/10.1093/jopart/muaa031

Michener, G. (2015). Policy Evaluation via Composite Indexes: Qualitative Lessons from International Transparency Policy Indexes. World Development, 74, 184–196. https://doi.org/10.1016/j.worlddev.2015.04.016

Ministry of Development. (2020). Auxílio Emergencial 2020. Secretaria De Avaliação E Gestão Da Informação - Sagi. https://aplicacoes.mds.gov.br/sagi/vis/data3/?g=2

Moynihan, D., Herd, P., & Harvey, H. (2015). Administrative Burden: Learning, Psychological, and Compliance Costs in Citizen-State Interactions. Journal of Public Administration Research and Theory, 25(1), 43–69. https://doi.org/10.1093/jopart/muu009

Nisar, M. A. (2018). Overcoming resistance to resistance in public administration: Resistance strategies of marginalized publics in citizen-state interactions. Public Administration and Development, 38(1), 15–25. https://doi.org/10.1002/pad.1817

Pathki, C. S., Kluemper, D. H., Meuser, J. D., & McLarty, B. D. (2021). The Org-B5: Development of a Short Work Frame-of-Reference Measure of the Big Five. Journal of Management, 014920632110026. https://doi.org/10.1177/01492063211002627

Peeters, R. (2019). The Political Economy of Administrative Burdens: A Theoretical Framework for Analyzing the Organizational Origins of Administrative Burdens. Administration & Society, 52(4), 566–592. https://doi.org/10.1177/0095399719854367

Peeters, R. (2023). Digital Administrative Burdens: An Agenda for Analyzing the Citizen Experience of Digital Bureaucratic Encounters. Perspectives on Public Management and Governance, 6(1), 7–13. https://doi.org/10.1093/ppmgov/gvac024

Peeters, R., & Widlak, A. (2018). The digital cage: Administrative exclusion through information architecture – The case of the Dutch civil registry’s master data management system. Government Information Quarterly, 35(2), 175–183. https://doi.org/10.1016/j.giq.2018.02.003

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of Method Bias in Social Science Research and Recommendations on How to Control It. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452

Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072

Samuels, D. J., & Zucco, C. (2013). Using Facebook as a Subject Recruitment Tool for Survey-Experimental Research. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2101458

Srivastava, M., Heidari, H., & Krause, A. (2019). Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2459–2468. https://doi.org/10.1145/3292500.3330664

Suh, H., Shahriaree, N., Hekler, E. B., & Kientz, J. A. (2016). Developing and Validating the User Burden Scale: A Tool for Assessing User Burden in Computing Systems. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 3988–3999. https://doi.org/10.1145/2858036.2858448

Tabachnick, B. G., & Fidell, L. S. (2001). Using Multivariate Statistics (Fourth Edition). Allyn & Bacon.

Thomsen, M. K., Baekgaard, M., & Jensen, U. T. (2020). The Psychological Costs of Citizen Coproduction. Journal of Public Administration Research and Theory, 30(4), 656–673. https://doi.org/10.1093/jopart/muaa001

Veale, M., & Brass, I. (2019). Administration by Algorithm? In K. Yeung & M. Lodge (Eds.), Algorithmic regulation (1st ed., pp. 121–149). Oxford University Press.

Watson, D., Anna, L., & Tellegen, A. (1988). Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales. Journal of Personality and Social Psychology, 54(6), 1063–10170. https://doi.org/10.1037/0022-3514.54.6.1063

Yeung, K. (2019). Why Worry about Decision-Making by Machine? In Algorithmic regulation (1st ed., pp. 21–33). Oxford University Press.

Zouridis, S., van Eck, M., & Bovens, M. (2020). Automated Discretion. In P. Hupe & T. Evans (Eds.), Palgrave handbook on discretion: The quest for controlled freedom (1st ed.). Palgrave Mcmillan.

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Publicado

2023-10-09

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Marinho, M. (2023). Desafios na interação digital dos cidadãos com o Estado: uma escala para medir os obstáculos administrativos. Revista Do Serviço Público, 74(3), 591-612. Recuperado de https://revista.enap.gov.br/index.php/RSP/article/view/9890

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