Managerial and Operational Hindrances to Polio Eradication: A Case Study of Tehsil Katlang, Mardan, Pakistan
Bibliographic record
Abstract
The study aims to analyse managerial and operational hindrances to polio eradication process in Tehsil Katlang, District Mardan using quantitative research method i.e. questionnaire and statistical analysis. A sample size of 200 respondents i.e. polio workers of health department, staff of WHO and UNICEF are selected through proportionate stratified random technique. Bi-variate analyses are conducted with the help of Chi-square test. The study results concludes a significant association between polio eradication process and maintenance of cold chain, lack of transportation facility to polio staff, accessibility with reference to locality, training opportunities of polio workers, lack of trained public health professionals, workers dissatisfaction from salaries, timely payment of NIDs remuneration, unnecessary bureaucratic interventions and influences in Expended Program on Immunisation (EPI), lack of proper evaluation of National Immunisation Days (NIDs) campaign and security threats to polio workers. Further, a non-significant association is ascertained between polio eradication and timely availability of vaccines to EPI workers, effects of load shedding on maintenance of cold chain and proper monitoring of NIDs campaign. The findings state that the program needs proper management process for cold chain and transportation facilities. Salaries of the workers need to be increased and NIDs remuneration needs to pay on time. Various training programs should be initiated for workers and shortage of staff should be removed. Security arrangements for polio workers may be enhanced.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".