E-Participation and Citizen Relationship Management in Urban Governance
Bibliographic record
Abstract
Citizen relationship management (CiRM) is a combination of management approaches and information technologies for improving citizen services and citizen participation used at all levels of government. As an adaptation of private sector customer relationship management (CRM), CiRM is experiencing significant public sector adoption rates globally. However, while private sector CRM has demonstrated significant impact in the private sector, CiRM benefits are limited, and particularly lagging in the area of citizen e-participation in urban governance. This chapter provides an overview of the scope of CiRM functionality, with particular regard to the CRM origins and CiRM extensibilities, to develop a broader perspective of CiRM’s capacity for addressing e-participation. Developing this perspective further, theoretical and methodological approaches to e-participation are presented and evaluated in four categories: generic CiRM participation models, e-government CiRM, democratic CiRM, and strategic CiRM. Further research opportunities are highlighted within the context of emerging organizational, technological, and societal trends.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".