Organization and (<scp>D</scp>e)mobilization of Farmworkers in <scp>Z</scp>imbabwe: Reflections on Trade Unions, <scp>NGOs</scp> and Political Parties
Bibliographic record
Abstract
This paper examines the ‘labour question’ in light of the wider agrarian questions, with a focus on the ways to understand activities of trade unions, NGOs and political parties as key actors in seeking to mobilize farmworkers. Drawing on research on farmworkers in Zimbabwe and engaging with literature concerning farm labour in the drastic changes to large‐scale agriculture in this country since 2000, the paper emphasizes the importance of examining the wider terrain of politics that influences the actions and abilities of extra‐farm organizations to operate with farmworkers. Through critically engaging with the wider literature concerning the political economy of farm labour, the paper proposes the importance of attending to what it calls the ‘cultural politics of belonging’, which strongly shapes both the forms of attachment of farmworkers and farm dwellers to the farms and the strategies of mobilization and demobilization taken by these organizations. Through attending to such relationships and the wider terrain of politics, this paper proposes an alternative analysis to those currently found in the polarized literature on farmworkers and the Fast Track Land Redistribution Programme in Zimbabwe.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".