The impact of single window system on customs administration at Victoria falls border post in Zambia
Bibliographic record
Abstract
Zambia Revenue Authority Act Number 23 of 1994 mandates Customs to manage export and import formalities for international trade. In Zambia, there has been poor customs administration due to numerous pieces of legislations which conflict in their implementations. In the recent past the Zambian government has strived to improve Boader formalities through the introduction of the Single Window System (SWS) which cuts down on a number of formalities but integrates them into a single window with various components including information communication technology (ICT), trade regulation (TR) and trade facilitation (TF). In this study, the researcher used a deducted approach to test the relationship between Single Window System and Customs administration. Data was collected using a survey method and 350 respondents comprising various stakeholders at Victoria Boarder answered a questionnaire. The study showed overall that ICT, TR and TF sit statistically Significant to determining Customs Administration and therefore is a significant predictor of customs administration. However, the coefficient results show that ICT is not a predictor of customs administration and was marred with lots of poor internet connectivity and lack of electricity. The study recommends an improvement of internet facility and improved energy source since the single window system is anchored in ICT. Further, the study recommends that staff must be trained in various aspects of single window administration.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".