Algorithmic formalization
Impacts on administrative processes
Bibliographic Data
| ID | 6446564 |
|---|---|
| Authors | Antonio Cordella (0000-0002-4468-7807, London School of Economics and Political Science London UK), Francesco Gualdi (0000-0003-0449-9884, London School of Economics and Political Science London UK, corresponding author) |
| Year | 2024 |
| Volume | 103 |
| Issue | 2 |
| Pages | 441-466 |
| Publication date | 2024-08-27 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Administration (JOURNAL) |
| Journal identifiers | ISSN: 0033-3298 • E-ISSN: 1467-9299 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/padm.13030 |
| OpenAlex | W4401916482 |
| Language | EN |
| Citations received | 8 |
| References cited | 59 |
This paper investigates the influence of algorithms on the administrative processes within public organizations, utilizing the foundational theory of formalization from Walsh and Dewar (1987) as a framework. Introduces the concept of “algorithmic formalization”, a new form of formalization induced by the adoption of algorithms, which fundamentally alters administrative workflows. Focusing on COMPAS algorithm used in the US judiciary for risk assessment, the paper illustrates how the algorithm serves multiple roles – as code, channel, and standard – systematizing administrative processes related to risk assessment and judicial decisions. By delving into COMPAS case study, the research sheds light on the novel concept of algorithmic formalization, emphasizing its significant repercussions for analyzing and applying algorithmic administrative processes
Business · Blockchain Technology Applications and Security · Computer Science · Ethics and Social Impacts of AI · Legal and Policy Issues
AI Public Value Creation
Fairness Perception, Administrative Burden, and Social Welfare Participation
Digital surveillance governance
Algorithmic Governance
A Replication of “Explaining Why the Computer Says No
Holding AI Accountable Like Herding Cats
From Discretion to Calculation
Public Encounters and Government Chatbots
Machines Who Think
Media Technologies
Managing Artificial Intelligence
Artificial Intelligence in Organizations
Ethical Implications and Accountability of Algorithms
Fair Prediction with Disparate Impact
Economy and Society
The Dark Sides of Artificial Intelligence
Artificial Discretion as a Tool of Governance
Qualitative Case Study Methodology
New Public Management
Artificial Intelligence in Government
Artificial intelligence and speedy trial in the judiciary
Mapping the challenges of Artificial Intelligence in the public sector
Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision making
Opportunity for renewal or disruptive force? How artificial intelligence alters democratic politics
Computing the everyday
Social Equity
Assessing Qualitative Studies in Public Administration Research
Public Administration Challenges in the World of AI and Bots
The New Public Service
The future of public administration research
Assessing public value failure in government adoption of artificial intelligence
Can details depoliticize? An examination of the formalization strategy
How rediscovering nodality can improve democratic governance in a digital world
Algorithms in the public sector. Why context matters
A machine learning approach to open public comments for policymaking
Explaining Why the Computer Says No
Accountable Artificial Intelligence
Algorithmization of Bureaucratic Organizations
Digital Government, Open Architecture, and Innovation
Urban E-Government Initiatives and Environmental Decision Performance in Korea
Comparing Public and Private Organizations
Artificial intelligence, bureaucratic form, and discretion in public service
Algorithmic transparency and bureaucratic discretion
Big Data and AI – A transformational shift for government
Collaboration and Leadership for Effective Emergency Management
A Public Management for All Seasons
| Unique citing works | 8 |
|---|---|
| Citations per year | 8 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 8 |