Research informing practice: Toward effective engagement in community ICT in New Zealand
Bibliographic record
Abstract
New Zealand’s Computers in Homes has been researched since its inception in 2000, through both participatory action research and multiple mixed methods case studies, by the authors of this paper who are now collaborating to find the most meaningful way to assess social outcomes in the scheme as it evolves. Computers in Homes (CIH) not only continues to be informed by the research but it is also beginning to make use of social media for community participant engagement. This paper traces the inter-relationship between the ongoing research and evolution of practice, reflecting on a shift in epistemology and thus research design. Our work now extends to explore the relationship between community blogging, adopted by CIH as a way of engaging the community in making sense of their own experience and thus owning their own research, and the role of social relationships in facilitating a sense of belonging. Our paper examines how the use of social media in this way may challenge the more traditional ideas and power relations inherent in the researcher-participant relationship in community ICT research.
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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 | 0.085 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.004 | 0.004 |
| 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".