O abandono estratégico : o campesinato angolano sob a dominação da MPLA
Bibliographic record
Abstract
Angola’s colonial past has served as a symbolic lodestar for the government’s plans reimagining the future spaces of the countryside. However, a confluence of historical influences and partisan political aims has weighed heavy on the plans behind revitalizing the sector to the detriment of agricultural production and rural Angolans alike. With the agricultural sector as its backdrop, we attempt to expose how the government’s illiberal peacebuilding model has intentionally used its prolonged ‘socialist’ presence in the rural economy to stunt private economic initiatives, deprived its peripheral populations of public resources, and only significantly invested in segmented areas where resource control remained within elite channels of influence. This strategy effectively abandoned large swathes of rural communities, though the monopoly hold on the power of resource distribution was broken down with the arrival of Non-State Actors in the countryside. The entrance of this new element allowed for the strengthening of the capacity of endogenous rural agency, exemplified by the formation of Rede Terra and its national campaign to influence the latest land law. Domination through abandon has proven an effective strategy of imposing its authority where it remains the weakest, though any real attempt at economic diversification would require a more popular approach. It remains to be seen whether the government is willing to renounce its strategy of domination.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".