Relational Work Is the Work: Virtual Healthcare Transformation for Rural, Remote and First Nations Communities in British Columbia
Bibliographic record
Abstract
Contextualizing the Healthcare CrisisCanada is in the midst of a healthcare crisis, which is exacerbated in populations living in rural, remote and First Nations communities (Greenwood et al. 2018;Sibley and Weiner 2011;Wilkinson et al. 2015).There are welldocumented disparities between rural and urban populations when it comes to access to health services and overall health outcomes, which are influenced by the determinants of health and a number of other factors, including expansive geography, transportation, climate hazards and provider recruitment and ABSTRACTThe healthcare crisis across unceded First Nations' territories in rural, remote and Indigenous communities in British Columbia (BC) is marked by persistent barriers to accessing care and support close to home.This commentary describes an exceptional story of how technology, trusted partnerships and relationships came together to create an innovative suite of virtual care programs called "Real-Time Virtual Support" (RTVS).We describe key approaches, learnings and future considerations to improve the equity of healthcare delivery for rural, remote and First Nations communities.The key lessons include the following: (1) moving beyond a biomedical model -the collaboration framework for health service design incorporated First Nations' perspective on health and wellness; (2) relational work is the work -the RTVS collaboration was grounded in building connections and relationships to prioritize cultivating trust in the partnership over specific outputs; and (3) aligning to the core values of co-creation -working from a commitment to do things differently and applying an inclusive approach of engagement to integrate perspectives across different sectors and interest groups.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.041 | 0.027 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".