Embedding Digital Advantage: A Five-Stage Maturity Model for Digital Communities
Bibliographic record
Abstract
Information and Communications Technology (ICT) has the potential to offer citizens new ways with which to engage in the process of democracy. It is not sufficient that communities and citizens have access to ICT for the digital divide to be bridged; such communities need to also become literate in the new technologies. Resources need to be made available that are useful, interesting and relevant. Ultimately, communities need to be empowered to become more than receivers of information and services via technology; they must become producers of new knowledge and information. Such publications are then able to represent a community’s unique viewpoint to a wider audience. This paper describes a five stage model for community ICT engagement and maturity. This model is non-linear and temporal and can be used as an audit of current community technology capability for assessing maturity and for establishing clear milestones within a community ICT framework. Such a model is useful for assessing and developing eDemocracy issues within individual groups and communities and as a way of mapping progress within a wider community, city or regional setting.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".