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Record W2027569907 · doi:10.1177/0275074013487943

Implementing a Revenue Authority Model of Tax Administration in Ghana

2013· article· en· W2027569907 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe American Review of Public Administration · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTax administrationTax reformRevenueDeveloping countryTax revenueBusinessPublic economicsAdministration (probate law)EconomicsProcess (computing)Tax avoidancePublic administrationEconomic policyFinanceEconomic growthPolitical scienceLaw

Abstract

fetched live from OpenAlex

The desire to increase domestic revenue mobilization has made tax reform a priority for governments in many developing countries. Addressing the tax problem, however, is often a complex process that involves reforming the tax system, as well as setting up effective administrative structures to administer that system. Many see the revenue authority (RA) model as the solution to these problems. Developing an RA model in Ghana began in the mid 1980s; it was not, however, fully operational and integrated until 2010. Using social learning theory, we argue that Ghana’s successful readoption of the RA model can be attributed to the lessons learned both in its own first attempts and from the successful tax reform experiences of other countries.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.080
GPT teacher head0.315
Teacher spread0.235 · 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