Social Capital and Community Networking: Ethno-cultural Use of Community Networking Initiatives
Bibliographic record
Abstract
Under the umbrella of the SSHRC funded Canadian Research Alliance for Community Innovation and Networking (CRACIN) research study, this paper examines issues of social capital, social inclusion and cohesive and sustainable communities for new immigrants within the context of the federal government’s various Community Networking (CN) initiatives. The first of a two part study, this paper provides a theoretical background to the following questions: i)What do we mean by social capital and information communication technology?; and ii)What do we mean by Community Informatics? Lastly, this paper proposes a research framework on the methodology of how to measure and analyze these questions. In essence, this study seeks to answer the following question: Has providing technical ‘connectedness ’ via public access to community-oriented internet services promoted sustainable social, cultural and economic ‘connectedness ’ and development for Canada’s new immigrants and ethno-cultural communities? 2 This study is an attempt at examining the potential for ICTs as an enabling tool for the development of social capital in the creation of more cohesive and sustainable communities.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".