ICT Infrastructure as Public Infrastructure: Exploring the Benefits of Public Wireless Networks
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
To date, research on municipal and community wireless networks has focused on understanding types of network deployments, policy issues around network ownership, and technical issues of infrastructure design and capability. These are all necessary issues as this nascent form of public infrastructure becomes established, and as stakeholders understand the potential benefits of the deployment and use of wireless networks. However, public wireless network deployments do not always achieve the desired outcomes, resulting in networks that do not realize their potential value for citizens, communities and municipalities. As such, it is also important to consider the extent to which such public infrastructure actually does deliver on its promises, by developing a set of criteria with which to assess public network deployments. This paper presents a “desiderata ” for public wireless internet infrastructure. Developed from our understanding of the potential of wireless networking, the desiderata is intended to provide a foundation for a discussion of what public wireless networks should look like. The paper also outlines some enabling conditions that can help to establish public networks to meet the needs of citizens, communities and municipalities. 2
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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