Doing more among institutional boundaries: Platform‐enabled government in China
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 The concept of Government as a Platform (GaaP) has recently encountered setbacks in practice worldwide. While existing literature on inter‐governmental collaboration has emphasized organizational restructuring and data sharing, this study argues that a pragmatic way to improve administrative efficiency in the absence of formal institutional change is to adopt an alternative model to GaaP: platform‐enabled government. Enabled by innovations of the middle‐tier platform, this new model of platform governance integrates the functions of distributed systems of multiple departments into a sequential workflow without the requirement of institutional reform or sharing proprietary data. To demonstrate how this model facilitates information flow across institutional boundaries and improves collaborative governance, we analyze horizontal, vertical, and public‐private collaboration using a diverse case study design. We examine administrative review, law enforcement, and contact tracing during the pandemic in the context of China. Our findings suggest accommodating institutional boundaries is a practical and effective approach to advance the digital government agenda in decentralized contexts.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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