Power, Communities, and Community Informatics: a meta-study
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
In this paper we tackle the theme of power in the context of communities and Community Informatics through addressing five questions.What is power? What is empowerment?In what ways is it exercised?How does all of this pertain to communities?How does all of this pertain to Community Informatics?The first three questions are addressed through reference to well known propositions drawn from social theory, and having established this background, the last two questions are foregrounded through a content analysis meta-study of the abstracts of papers submitted to the 2009 Prato Community Informatics Conference. The overarching theme of this conference was power and empowerment in community informatics ruixkkcdc In this paper we tackle the theme of power in the context of communities and Community Informatics through addressing five questions. What is power?What is empowerment?In what ways is it exercised?How does all of this pertain to communities?How does all of this pertain to Community Informatics? The first three questions are addressed through reference to well known propositions drawn from social theory, and having established this background, the last two questions are foregrounded through a content analysis meta-study of the abstracts of papers submitted to the 2009 Prato Community Informatics Conference. The overarching theme of this conference was power and empowerment in community informatics.
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 | 0.025 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.000 | 0.006 |
| 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