Advancing Public Trust Relationships in Electronic Government: The Singapore E-Filing Journey
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
E-governments have become an increasingly integral part of the virtual economic landscape. However, e-government systems have been plagued by an unsatisfactory, or even a decreasing, level of trust among citizen users. The political exclusivity and longstanding bureaucracy of governmental institutions have amplified the level of difficulty in gaining citizens' acceptance of e-government systems. Through the synthesis of trust-building processes with trust relational forms, we construct a multidimensional, integrated analytical framework to guide our investigation of how e-government systems can be structured to restore trust in citizen-government relationships. Specifically, the analytical framework identifies trust-building strategies (calculative-based, prediction-based, intentionality-based, capability-based, and transference-based trust) to be enacted for restoring public trust via e-government systems. Applying the analytical framework to the case of Singapore's Electronic Tax-Filing (E-Filing) system, we advance an e-government developmental model that yields both developmental prescriptions and technological specifications for the realization of these trust-building strategies. Further, we highlight the impact of sociopolitical climates on the speed of e-government maturity.
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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 | 0.020 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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