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Record W3144189232 · doi:10.1017/cbo9781316275511

Taxation, Responsiveness and Accountability in Sub-Saharan Africa

2015· book· en· W3144189232 on OpenAlexaff
Wilson Prichard

Bibliographic record

VenueCambridge University Press eBooks · 2015
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAccountabilityCorporate governancePoliticsDeveloping countryBargaining powerFoundation (evidence)Public economicsPolitical sciencePower (physics)EconomicsDiversity (politics)Tax reformDevelopment economicsEconomic growthFinance

Abstract

fetched live from OpenAlex

It is increasingly argued that bargaining between citizens and governments over tax collection can provide a foundation for the development of responsive and accountable governance in developing countries. However, while intuitively attractive, surprisingly little research has captured the reality and complexity of this relationship in practice. This book provides the most complete treatment of the connections between taxation and accountability in developing countries, providing both new evidence and an invaluable starting point for future research. Drawing on cross-country econometric evidence and detailed case studies from Ghana, Kenya and Ethiopia, Wilson Prichard shows that reliance on taxation has, in fact, increased responsiveness and accountability by expanding the political power wielded by taxpayers. Critically, however, processes of tax bargaining have been highly varied, frequently long term and contextually contingent. Capturing this diversity provides novel insight into politics in developing countries and how tax reform can be designed to encourage broader governance gains.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.212
Teacher spread0.159 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations147
Published2015
Admission routes1
Has abstractyes

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