The Zimbabwean People's Army moment in Zimbabwean history, 1975–1977: Mugabe's rise and democracy's demise
Bibliographic record
Abstract
This article provides a historical analysis of Robert Mugabe's rise to power in the fractious hierarchy of the Zimbabwe African National Union (ZANU), in part by crushing all opposition and manipulating regional and international actors – including British, American and Mozambican political leaders – into supporting his claims to leadership. It also tells an often-ignored story of internal political struggle during the liberation war involving a small group of young political soldiers, the Zimbabwean People's Army (ZIPA), which challenged the policies, practices and ideology of the ‘old guard’ and tried to unify ZANU and Zimbabwe African People's Union, the country's two nationalist movements at the time. Drawing on interviews and extensive archival data, the article argues that ideology was central to this political struggle; ZIPA embraced a more radical and potentially more democratic vision for the liberation movement and for the future of the country. What kind of regime might have been consolidated in post-independent Zimbabwe if ZIPA had succeeded in unifying the country's national liberation movement and pushing them into the political direction ZIPA desired? This will never be known. By 1977, less than two years after the group emerged, its leaders were imprisoned in Mozambique's jails where they would remain until just prior to Zimbabwe's first democratic election in 1980.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| 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".