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Full-Text Articles in Social and Behavioral Sciences
Exploring The Potential Of E-Government In Reducing Corruption – Case Of Egypt, Mahinour Abou Elseoud
Exploring The Potential Of E-Government In Reducing Corruption – Case Of Egypt, Mahinour Abou Elseoud
Theses and Dissertations
Many countries have recognized the significance of electronic work transition to application, frequently known as e-government, with the purpose of improving their bureaucratic performance and reducing corruption. From an economic standpoint, transparency may boost government efficiency as it increases the government capacity and, eventually, fosters good governance by reducing corruption and inefficiency. As a result, this study aims to analyze the correlation between e-government and corruption, as well as whether e-government reduced the detrimental effects of corruption on public trust. To accomplish this objective, the thesis focuses on in-depth interviews with citizens of all ages, socioeconomic and educational backgrounds, as …
Administrative Law In The Automated State, Cary Coglianese
Administrative Law In The Automated State, Cary Coglianese
All Faculty Scholarship
In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
All Faculty Scholarship
Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …
Tweeting The Government: Preliminary Findings From A Genre Analysis Of Canadian Federal Government Tweets, Elizabeth M. Shaffer, Luanne Freund, Mackenzie Welch
Tweeting The Government: Preliminary Findings From A Genre Analysis Of Canadian Federal Government Tweets, Elizabeth M. Shaffer, Luanne Freund, Mackenzie Welch
Elizabeth M. Shaffer
Social media is rapidly becoming an integral part of the Canadian Federal Government’s communication plan. Its use has been institutionalized with the adoption of the Guidelines for External Use of Web 2.0, which provides policy guidelines for government agencies on using social media tools. Twitter, a microblogging site, has rapidly gained popularity with Canadian government agencies. The primary purpose of this research is to identify the communicative intents behind federal government agencies’ use of Twitter. A random set of 2,000 tweets were collected over a one month period in 2012 and were coded using a schema derived from both relevant …