The Role of Tax Administration in Shaping SME Performance in Lae, Papua New Guinea
Bibliographic record
Abstract
The objective of the study is to evaluate how the role of tax administration in shaping SME performance in Lae City, Papua New Guinea. The social, legal, economic, and environmental reasons taxpayers want to abide by the tax system's rules. The current tax benefits, such as free zone incentives, income tax exemptions, double taxation agreements, capital gains exemptions, and import duty exemptions, do not currently support the expansion of SMEs. The study sampled 100. Purposive sampling was used to select the community sample in this study to obtain accurate results. The tax collection of small and medium enterprises (SMEs) is crucial for a country's economic growth and development. Governments should consider simplifying tax legislation and provide instruction in simple terms. Ensure the tax rates for SME’s are reasonable and competitive. In Addition to that SME’s must minimize their tax liability and engage in the tax planning and regularly adjusting and reviewing the structure of the business can efficiently help tax to optimize, by hiring and consulting the tax professionals can be more helpful to small-medium enterprise to help navigate the difficult tax codes and to reduce risk of non-tax compliances. SME association should engage with tax authorities to get feedback and better comprehend the particular needs and challenges faced by SMEs in the field of taxation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".