Impact of Human Development Indicators on Child Mortality: The Case Study of Iran
Bibliographic record
Abstract
The mortality rate of children under the age of five is of particular importance, as it is often related to the general level of health and living standard condition of the household in the society. The study aimed to investigate the effects of the Human Development Index on public health with particular reference to the under-five mortality rate in Iran. As a method a descriptive-analytical method including ordinary least square regression analysis was used to identify the causal relationship between the human development index and the under-five mortality rate during the period of the study (1987-2017) in Iran. The results show that there is a negative and meaningful relationship between the human development index (HDI) level and the under-five mortality rate. Moreover, the control variables including inflation rate, unemployment rate, and income distribution inequality index showed a positive and meaningful impact on the under-five mortality rate. Given that human capital is considered the engine of economic growth and development, it can be concluded that any increase in health expenditures through improvements in human capital inventory leads to increased economic growth, increased life expectancy, and decreased under-five mortality rate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".