Ghana’s 2020 General Elections: An Assessment of the Journey and Processes
Bibliographic record
Abstract
Abstract The December 7, 2020 General Election was the 8th milestone in Ghana’s electoral politics. It was keenly competitive for several reasons, including the fact that the two key contenders had a sense of unfinished agenda and wanted to capture or hold on to power to complete what had been initiated. The flag bearer of the main opposition party was voted out after one term in power, in a manner that challenged the creeping belief that all regimes in Ghana, since 1992, serve two terms in office. Whereas the ruling party did all it could to maintain the two-term tradition, the main opposition party also did its best to drum home the message that, the two-term tradition is not yet institutionalized. It was also widely believed that a defeat of any of the two main contenders, may mark the end of their respective political careers, as the two main political parties would file completely new candidates in future elections. This paper seeks to examine the journey and processes towards the 2020 General Elections within the context of the global pandemic, COVID-19. The paper highlights and fleshes out all the major issues before and during the elections and proffers possible explanations on the outcome of the elections.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".