Bibliographic record
Abstract
The study examined the effect of E-taxation adoption on revenue generation in Nigeria.Specifically, the study assessed the effect of E-taxation on Company Income Tax (CIT) and Value Added Tax (VAT).Expo facto research design was adopted and data were sourced from Federal Inland Revenue Service.The study period covered six (6) years and three (3) quarters, spanning from the first quarter of 2012 to the second quarter of 2018.The study was on quarterly bases and the period for pre-E-taxation covered thirteen (13) quarters, spanning from the first quarter of 2012 to the first of 2015 while the period for post E-taxation covered thirteen (13) quarters, spanning from the second quarter of 2015 to the second quarter of 2018.The analysis that was carried out through paired sampled t-test revealed a positive insignificant difference between pre and post company income tax revenue with t-statistics and p-value reported to be 0.833 and 0.421 respectively; and that there was a positive insignificant difference between pre and post value added tax revenue with t-statistics and pvalue of 0.520 and 0.612 respectively.It was concluded that E-taxation has not significantly spur revenue generation in Nigeria.Thus, the study recommended that federal government through Federal Inland Revenue Services should work out modalities on how to sensitize companies on the nitty-gritty of E-tax payment so as to maximize the expected positive impact of the initiative and that Federal Inland Revenue Services must ensure that the website is of good quality and accessible to all and sundry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".