Bibliographic record
Abstract
Drawing on community expertise, open-source software and non-hierarchical organizational strategies, community wireless networks (CWN) engage volunteers in building networks for public internet access and community media. Volunteers intend these networks to be used to reinvigorate local community. Together the following two purposes create two distinct mediated publics: to engage volunteers in discussing and undertaking technical innovations, and to provide internet access and local community media to urban citizens. To better address the potential of CWN as a form of local innovation and democratic rationalization, the relationship between the two publics must be better understood. Using a case study of a Canadian CWN, this article advances the category of ‘public’ as alternative and complementary to ‘community’ as it is used to describe the social and technical structures of these projects. By addressing the tensions between the geek-public of WiFi developers, and the community-public of local people using community WiFi networks, this article revisits questions about the democratic impact of community networking projects. The article concludes that CWN projects create new potential for local community engagement, but that they also have a tendency to reinforce geek-publics more than community-publics, challenging the assumption that community networks using technology development as a vector for social action necessarily promote greater democracy.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.171 | 0.025 |
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".