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Record W1977638918 · doi:10.1017/s0021855305000124

IMPROVING TAX ADMINISTRATION: A CASE STUDY OF THE UGANDA REVENUE AUTHORITY

2005· article· en· W1977638918 on OpenAlexaff
Jalia Kangave

Bibliographic record

VenueJournal of African Law · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRevenueTax revenueAdministration (probate law)BusinessTax administrationPublic economicsPovertyProduct (mathematics)Internal revenueTax reformEconomicsAccountingEconomic growthPolitical scienceMarketingLaw

Abstract

fetched live from OpenAlex

KANGAVE, JALIA, Improving tax administration: a case study of the Uganda Revenue authority, Journal of African Law , 49 , 2 (2005): 145–176 The prevalence of poverty in developing countries demands that these countries should improvise internal revenue generating projects to supplement, or better still, ultimately significantly reduce dependence on foreign funding. This way self-sustaining economies will be built. One such internal revenue-generating mechanism, and perhaps the most commonly used, is taxation. This paper makes a case for tax administration as a tool of increasing the contribution of tax revenue to Gross Domestic Product, and consequently, a means of reducing the gap between the rich and the poor. The goal of this paper is to propose ways in which the Uganda Revenue Authority (the URA) can improve its tax administration. To achieve this objective, the paper begins with a detailed discussion of the URA's structure and the procedures it follows in collecting taxes. It then highlights the problems that may arise from such structure and procedures, before making proposals on how the URA can reform its organizational structure and processes to maximize its potential in revenue collection capabilities.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.261
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2005
Admission routes1
Has abstractyes

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