Bibliographic record
Abstract
In the modern world, the phenomenon of economic inequality between citizens in a state is increasingly observed. This situation appears with different intensity in each country depending on its economic and social background and the organization it has as a welfare state. It is characteristic that the negative effects of the phenomenon are faced also by developed countries such as the USA, Canada, Germany, Japan, etc. Research has shown that social and economic inequalities also have a significant effect on a country's child and infant mortality rate. This fact highlights the need for further study of the phenomenon and the coordinated effort that must be made by the states to eliminate it. Based on the above, we used data from 36 developing countries for the year 2010, in order to check whether the significant effect of economic inequalities on infant and child mortality rates is confirmed. In our sample we have a list of developing countries to examine. The simple and multiple linear regression models were used for the analysis of our data. We have selected key economic variables as independent variables that are widely used in similar analyzes, coming up with interesting conclusions about the phenomenon.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.315 |
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; both teacher heads agree on what is shown here.
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".