CARI guidelines: Culturally safe and clinical kidney care for First Nations Australians – A summary
Bibliographic record
Abstract
ContextThe 'inaugural' Caring for Australian and New Zealanders with Kidney Impairment (CARI) guidelines for First Nations Australians provide recommendations on caring for First Nations Peoples with chronic kidney disease (CKD).Informed by targeted national community consultations, the guidelines include the historical context, detailed advice on culturally safe kidney healthcare, screening and referral of CKD.Public awareness and education initiatives, selfmanagement programs, and models of care are all reported on.Objectives The CARI guidelines were developed in response to significant challenges and inequities experienced by First Nations Peoples over many years.Specific recommendations and suggestions aim to improve clinicians' understanding of historical and contemporary factors contributing to the social and health inequities underpinning the over-representation of First Nations Peoples with CKD.These guidelines provide comprehensive support for health professionals in all service and care environments to better respond to the care needs of First Nations Peoples. Key findingsThe CARI guidelines highlight the need to provide culturally safe clinical care and explicitly cite the need to address institutional racism and improve cultural safety training for all renal service providers.They specifically recognise the importance of kinship, and equitable access to transport and accommodation services.They also focus on keeping people on Country where possible, including increased nurse-supported and Aboriginal health practitioner-supported dialysis services. ConclusionThe CARI guidelines provide recommendations on how to improve clinical kidney care delivery for and with First Nations Peoples by ensuring more responsive models of care.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".