Shuffled and Shortchanged? The Gender Gap in Cabinet Shuffles in Africa
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This article examines gendered patterns of cabinet appointments and shuffles by African heads of state. While a handful of previous studies have systematically analysed how regime type influences cabinet reshuffles in African autocracies, the gender dynamics of cabinet survival and replacement in the region remain underexplored. Using a cross-national dataset of 3,829 ministerial appointments from 1990 to 2021, I model the impact of individual-level factors on survival probabilities and cabinet shuffles. The findings reveal that women serve shorter tenures than men, even in high-prestige portfolios, but survival probabilities are not statistically related to gender when controlling for age, credentials, and political and socioeconomic factors. However, when cabinets are shuffled, women are significantly more likely than men to be succeeded by someone of the other gender. This study contributes to research on gender and cabinet politics by showing that, beyond political and socio-economic variables, individual-level factors significantly shape cabinet survival and shuffles in Africa.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it