Ripples in the water: a toolkit for Aboriginal people on hemodialysis.
Bibliographic record
Abstract
In 2004-2005, the authors were engaged in a community-based research study with people of Elsipogtog First Nation to determine the causes of and solutions to non-adherence among community members with chronic kidney disease. This study highlighted the need for a toolkit intended for Aboriginal people who are required to undergo hemodialysis at a dialysis unit in a city away from their rural community, so that they are sufficiently educated, supported and resourced to access and experience culturally relevant health care. This paper presents the findings of a two-year community-based research study to develop the prototype or model for such a toolkit. The research involved meeting with nine community members in group meetings at least monthly over the two years to determine what such a toolkit should include and how it should best be presented. It also entailed an extensive review of relevant literature and relevant educational materials, as well as individual interviews with key stakeholders. The project resulted in a culturally relevant toolkit that can be staged according to people's readiness for the information and that fosters collaborative discussions between patients, family members and health care practitioners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".