Determinants of Tax Compliance Behaviour under the Self-Assessment Scheme in Nigeria
Bibliographic record
Abstract
This study examined the determinants of tax compliance behaviour under the self-assessment scheme in Nigeria. A non-random stratified sampling technique was used to evaluate taxpayer behaviour. Data was also gathered using questionnaire from three of the six geopolitical zones in Nigeria, namely South-South, South-West and North central zones respectively. The specific locations were Edo state, Lagos state, and Federal Capital Territory, Abuja resulting in 550 respondents which were analysed. The results showed that tax audit and awareness of offences and penalties had a positive and significant impact on tax compliance behaviour under the self-assessment scheme in Nigeria. Simplicity of tax administration and returns, tax knowledge and taxpayers’ integrity had a positive but not significant impact on tax compliance behaviour under the self-assessment scheme in Nigeria. The study recommends that the tax authorities should enhance the capacity of tax audit and ensure that there are sufficient tax officials to facilitate tax audit exercise, create greater awareness of the various offences and penalties through the mass media and undertake an upward review of extant penalties.
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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 | 0.002 | 0.009 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".