Revisiting Electoral Violence in Zimbabwe: Problems and Prospects
Bibliographic record
Abstract
This study explores theoretical contradictions with realism, regarding the actors or perpetrators of violence when explaining the causes of electoral violence in the Zimbabwean context. These perspectives can be divided into two contesting schools of thought. The first group is mainly made up of rational theories and holds the position that, autocratic governments use electoral violence as a way of influencing electoral outcome. The second position suggests that the weaker political party is the one responsible for electoral violence. This paper then, contributes to the ongoing debate on the causes of electoral violence by advancing the notion that electoral violence should not be seen based on one position but from a multifaceted position. This is because, neither of the two theoretical approaches are wrong but what differs is the context. This paper argues that the idealism of holding one position hinders policy analysis to electoral violence, monitoring and observing election process as it places either, the ruling party or the opposition party as a unit of analysis.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".