Automating the Public Sector and Organizing Accountabilities
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
In this paper we examine the ways in which implementing new information and communication technologies (ICTs) to automate public sector processes affects accountability. New technologies alter conventional modes of behavior in the public sector, shedding light on certain areas of bureaucratic practice and obscuring others, and in doing so they enhance accountability and exacerbate dysfunctions. To investigate how ICTs influence the accountability equation, we explore a range of empirically documented e-government implementations, from simple transactions involving low-levels of automation to highly automated systems such as fingerprint analysis technologies. Drawing on these empirical examples, we develop a tentative framework of ICT-exacerbated accountability dysfunctions. Following this, we then discuss potential accountability arrangements for different types of e-government processes, in hope of realizing the benefits of new technologies while minimizing the potential for unaccountability and dysfunction that could arise from their application. Throughout, we stress the necessity of striking a balance between the potential benefits of ICTs to the bureaucratic process and systems that may reduce efficiency but uphold accountability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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