Perspectives on Telehealth Projects in Northern Communities: Lessons Learned for Decolonized Participatory Design and Assessment
Bibliographic record
Abstract
Northern and Indigenous communities face well documented challenges to accessing services and are impeded by significant infrastructure and technological limitations prompting the urgency to adopt innovative approaches to overcome these barriers. Telehealth – the means of accessing healthcare services and information across distance – promises to augment services to address access issues, yet notable utilization and structural constraints remain. Drawing on a recent community-based study capturing the perspectives from four Northern Saskatchewan communities on telehealth utilization, this paper draws attention to the importance of community collaborations as crucial to better decision-making and pathways forward. Specifically, this work identifies the need for decolonized participatory design (PD) and participatory technology assessment models that consider broader socio-cultural and technical factors to inform Indigenous technology design, adoption, and assessment for long-term community benefit. Further, to this is the need for community driven approaches and engagement through knowledge mobilization strategies that could better inform future community development.
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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 | 0.184 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.033 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.003 | 0.005 |
| 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".