Connecting Canadians: Investigations in Community Informatics
Bibliographic record
Abstract
Connecting Canadians represents the work of the Community Research Alliance for Community Innovation and Networking (CRACIN), the largest national and international research effort to examine the burgeoning field of community informatics, a cross-disciplinary approach to the mobilization of information and communications technologies (ICT) for community change. Funded for four years by the SSHRC's Initiative for the New Economy, CRACIN systematically studied a wide variety of Canadian community ICT initiatives, bringing perspectives from sociology, computer science, critical theory, women's studies, library and information sciences, and management studies to bear on networking technologies. A comprehensive thematic account of this in-depth research, Connecting Canadians will be an essential resource for NGOs, governments, the private sector, and multilateral agencies across the globe.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.021 |
| Science and technology studies | 0.068 | 0.018 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".