Implementing Digitalisation in an Administrative Justice Context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Administrative agencies have long been sites of technological innovation. Today, government officials worldwide are intensifying digitalization efforts to cut costs and to make bureaucratic operations more efficient. This article examines how digitalization initiatives are implemented in administrative settings, using examples from the United Kingdom (Universal Credit), Canada (Ontario’s Social Assistance Management System), and Australia (Online Compliance Initiative, a.k.a. ‘Robodebt’). It draws on qualitative research, government reports, and administrative justice literature to illustrate the dilemmas common to digital government projects. For example, digitalization both hardens and virtualizes the interface between officials and the public, while obscuring the vast amounts of human labour needed to maintain digital government initiatives. To function well, digital systems require deep integration between government databases and software. Yet, the process of digitalization is often piecemeal, continuous, and reproduces dilemmas that arise whenever new technologies are used to solve institutional problems. Consequently, the promised benefits of ‘digital by default’ initiatives are rarely realized. Digitalization accelerates a shift in relations between people and the state that administrative justice scholars must take seriously. First, scholars must reconsider the internal perspective from which administrative justice theories assess an outcome’s acceptability. Digitalization compels the development of new justice models centred on the values of system users within and outside of administrative institutions. Second, scholars must reassess administrative justice theory’s procedural focus. In digitalized settings, ‘administratively just’ decision-making processes may generate substantively unjust outcomes. These challenges must be addressed if administrative justice theories are to remain relevant in an age of algorithmically-driven decision-making.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it