Poverty and child (0–14 years) mortality in the USA and other Western countries as an indicator of “how well a country meets the needs of its children” (UNICEF)
Bibliographic record
Abstract
BACKGROUND: Children's (0-14 years) mortality rates in the USA and 19 Western countries (WCs) were examined in the context of a nation-specific measure of relative poverty and the Gross Domestic Product Health Expenditure (GDPHE) of countries to compare the effectiveness and efficiency of health care systems "to meet the needs of its children" (UNICEF). METHOD: World Health Organisation child mortality rates per million were analysed for 1979-1981 and 2003-2005 to determine any significant differences between the USA and the other WCs over these periods. Child mortality rates are correlated with all countries GDPHE and 'relative poverty', defined by 'Income Inequalities', i.e., the gap between top and bottom 20% of incomes. FINDINGS: Outputs: The mortality rate of every country fell substantially ranging from falls of 46% in the USA to 78% in Portugal. The highest current mortality rates are: USA, 2436 per million (pm), New Zealand 2105 pm, Portugal 1929 pm, Canada 1877 pm and the UK 1834 pm; the lowest are: Japan 1073 pm and Sweden 1075 pm, Finland 1193 pm and Norway 1200 pm. A total of 16 countries rates fell significantly more than the USA over these periods. Inputs: The USA had the greatest GDPHE and widest Income Inequality gap. There was no significant correlation between GDPHE and mortality but highly significant correlations with children's deaths and income inequalities. The five widest income inequality countries had the six worst rates, the narrowest four had the lowest. CONCLUSIONS: Despite major improvements in every WC, based upon financial inputs and child mortality outputs, the USA health care system appears the least efficient and effective in "meeting the needs of its children".
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".