Political Institutions and the Policy Process in Ghana: The Case of the Value-Added Tax (VAT).
Bibliographic record
Abstract
This paper seeks to explain differences in policy outcomes even when political institutions remain unchanged over time. It studies the making of Ghana’s most important fiscal policy after its transition to democracy in 1993. This study focuses on the making of the Value Added Tax (VAT) policy at two different time periods. In spite of unchanging political institutions, each episode, in 1995 and 1998, had a different outcome. This paper explores the extent to which the preferences of institutional actors can account for policy changes under the constraints and opportunities created by those same political institutions within the policymaking process. The paper employs George Tsebelis’ veto player theory, which emanates from the rational choice institutionalist school and argues that, when political institutions remain unchanged over time, changes in veto players’ preferences can account for changes in the policy outcome of the VAT.
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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 | 0.002 |
| 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 | 0.000 |
| 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".