Election petition and the future of electoral reforms in Ghana
Bibliographic record
Abstract
The results of Ghana’s 2012 and 2020 elections were challenged in the nation’s Supreme Court. Even though the court processes in both cases did not alter the election results, they nevertheless exposed monumental flaws in the electoral processes. The flaws in the 2012 electoral processes were exposed at the Supreme Court and featured in the final judgment of the court in a manner that allowed the Electoral Commission to initiate moves towards electoral reforms. However, the challenges of the 2020 elections, though exposed at the courts, were never featured in the final judgment of the Supreme Court. This paper discusses the implications of the 2020 election petition for the future of electoral reforms in Ghana. It argues that the rigid application of the letter of the law by the Supreme Court and the relegation to the background of the thorny issues of electoral challenges in the 2020 elections, would render the quest for further electoral reforms difficult. This would then make the future of any attempt to fine-tune the electoral processes quite bleak.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".