Building institutional trust through e‐government trustworthiness cues
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
Purpose Most theory and empirical research on the impact of e‐government on citizens' trust in government remains at the macro‐level and misses out on the complexities of the interaction between e‐services and citizens' trust in government. The purpose of this paper is to provide a deeper understanding of this complexity. Design/methodology/approach The research strategy is a comparative case study of two e‐services in Chile: a tax administration and an e‐procurement system. Data were collected from a variety of users (citizens and business owners) and public sector employees in the Araucania Region in Chile. Findings Within e‐services, the most easily perceived and influential trustworthiness cues are those outcomes that directly impact the citizen. These cues shape citizens' resultant interpretations of and trust in the public sector agency. Furthermore, the direction of this influence is mediated by individuals' particular circumstances and value positions. Key to understanding the process of building and destroying trust is the identification of the value conflicts that can emerge from e‐service implementations and how they align with citizens' values. Research limitations/implications The research conclusions are potentially an artefact of the financial nature of the e‐service transactions and the cultural uniqueness of Chileans. Originality/value The paper presents an original integrated conception of trust and institutional trust as well as a comparative analysis of citizens' perceptions and interpretations of “successful” e‐services.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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