Tonga Migrations: Ethnicity and Environmental Change Among Tonga Farmers of Zambia, a Reconnaissance
Bibliographic record
Abstract
Plateau Tonga farmers in Zambias Southern Province have been the subject of academic study for nearly 70 years and form part of a broader literature on the Tonga comprising upwards of 1200 sources. Yet there is one aspect of life that has evaded research. While migration from the Zambezi valley has long been examined, parallel processes from the plateau have been neglected since the 1940s. This paper seeks to advance research in this area, relying predominantly on interviews conducted with farmers and agricultural officers in Southern Province and Central Province in 2007 and 2008. I examine the reasons for migration, dynamics of family structure, and relations forged with local populations in host territories. Secondly, the paper considers changes in methods of production among migrants. Third, I assess some of the ways intimate aspects of social life are changing (religion, gender, inheritance practices and in-marriage). I examine ways the use of resources disproportionately impact people in the area. Finally, I examine the evolving meaning of Tonga identity, and its implications in national politics. The study of climate change and rapid ecological transformation provides insights into resource-driven migrations as well as ethnic and racial conflict in other parts of the continent.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".