Demographic characteristics and needs of families at an urban, low-income, multicultural paediatric clinic
Bibliographic record
Abstract
OBJECTIVES: To describe the demographic characteristics and identify the needs of a population attending an urban, low-income area, multicultural paediatric clinic. METHODS: Surveys were distributed to caregivers of children zero to 16 years of age (n=299). RESULTS: Of the children attending appointments, 55% were female and 51% were five years of age or younger. Of the caregivers, 29.5% were born outside of Canada and 25% reported that their primary spoken language was not English. Sixty-six per cent of families had been living in Edmonton for more than three years, with two-thirds of respondents living in Edmonton's second-lowest average household income region. Seventy-six per cent of respondents lived in households with four or more persons. CONCLUSIONS: Challenges facing individuals attending an urban, low-income area, paediatric clinic include language barriers, lower household income and larger family size. Immigrants living outside of major Canadian cities are under-represented and may have different needs compared with their counterparts in 'gateway' cities. More studies are needed to determine their needs, and will ultimately lead to the provision of culturally competent 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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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".