Determinants of Immunization Among Children Aged 12-23 Months in Ethiopia: A Proportional Odds Model Approach
Bibliographic record
Abstract
Childhood immunization is recognized as one of the most cost-effective public health interventions to prevent morbidity and mortality caused by infectious diseases, particularly in a high-endemic setting. According to the 2011 EDHS report by the Central Statistical Agency (CSA) of Ethiopia, nationally, only 24 percent of children age 12-23 months was fully immunized at the time of the survey. The main objective of this study was to identify and describe the determinants of immunization among children aged 12-23 months in Ethiopia. The source of the data was the Ethiopian Demographic and Health Survey conducted in 2011 (EDHS) 2011. In order to meet our objectives descriptive, and ordinal logistic regression (proportional odds model) statistical techniques were used for data analysis using socio-economic and demographic variables as explanatory variables and immunization status of children aged 12-23 months as the response variable. The results of the analysis predicts that place of delivery, wealth index, possession of radio and region were found to be significant determinants for full immunization among children aged 12-23 months in Ethiopia.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".