Characterizing the medical and social complexity experienced by Inuit children and their families from Nunavut who access care at an urban Canadian tertiary level paediatric hospital
Bibliographic record
Abstract
We aimed to characterise the medical and social complexities experienced by Inuit children and their families from Nunavut who were cared for at a general paediatrics clinic at an urban tertiary-level hospital located in Eastern Ontario. A retrospective chart review of this cohort was completed between 2016 and 2019. Two independent reviewers extracted data from charts. The cohort included 36 children, median (interquartile range [IQR]) age 13.5 (6.8, 28.2) months and full age range (1,140) months. They had a median (IQR) of 12.5 (7.8, 18.0) comorbidities, 11 (8.0, 14.2) healthcare services accessed and 3 (2, 5) medications. Almost all children (97.2%) had been hospitalised and the median number of days spent as an inpatient was 31.5. With respect to social complexity variables, 51.9% of clinical interactions (14 of 27 charts reviewed) at any point would have benefitted from an interpreter and 96.7% of 30 patient escorts/companions showed evidence of having difficulty in coping with homesickness. Improving social history taking and integrating screening for social determinants of health within the clinic should be considered. A dedicated interdisciplinary team approach focused on integrative care could be an effective method to improve communication and collaboration between service providers and with Inuit children and their families to reduce systemic health and social inequities.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".