Sustainable Community Technology: The symbiosis between community technology and community research
Bibliographic record
Abstract
The social sustainability of any community technology activity is dependent on whether or not it forms an integral part of, and contributes to, the shared experiences that constitute community life. Drawing from this premise the paper presents a human-centred exploration of community informatics (CI) by proposing that, as a field of study and practice, a central goal should be to develop shared understandings of ways in which ICT contribute to building and sustaining active and healthy communities. The diversity of community ICT practices have the potential to contribute to a collective knowledgebase that is not only of import as a resource for academic investigation but also in terms of its broader social significance to community life. With this in mind, the authors analyse and critically evaluate the significance of the emerging symbiosis between community technology and community research. Applying a human-centred perspective of CI to a community technology research and development project the paper concludes with a story about Black Elk, a Lakota shaman, as a metaphor for the relationship between community technology and community research.
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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.063 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".