Taxation Income, Graft and Informal Sector Operations in Nigeria in Relation to Other African Countries
Bibliographic record
Abstract
This study investigates the influence of the informal sector and graft on income accruing to the government through taxation in Nigeria. Informal economy and graft are the two critical activities that inhibit government tax revenue collection and negatively affect the performance of an effective government. The study employs secondary data that cover a period from 2000 to 2018.This period is the millennium period which the country is expected to overcome corruption and curtail the level of informal economic activities prevailing in the nation, but it appears that all efforts seem not to be yielding the required results. In order to achieve the objective of this study, the multi-regression analysis is performed and the results indicate that corruption is very harmful to tax revenue collection while the informal economy has no significant impact on tax revenue within the millennium period covered by this study. Thus, the study suggests formalization of legal unofficial economy activities and total eradication of corruption in Nigeria through the strengthening of the anti-graft agencies, reinforcement of the legal structure and introduction of a more severe penalty for the perpetrators.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".