An Assessment of the Impact of Corporate-Driven Foreign Land Investments on Selected Human Rights in Mozambique
Bibliographic record
Abstract
Abstract This article focuses on the impact of land investments in Mozambique. It examines the effects these land investments are having on local people’ access to food and sustenance, culture, land and water, and political engagement in some Mozambican provinces and areas. The next section critically evaluates whether human rights related to the aspects are being violated, as well as Mozambique’s legal obligations under both local and international law. The main goals are to alert the academic community to the negative impacts that land grab and investments have on local populations in Mozambique and to explain how these activities can be effectively stopped by using the normative framework now in place on human rights. It argues that foreign companies and investors in Mozambique are causing significant negative impacts on local communities, including livelihood, food, culture, land, and political participation. These issues are already protected by human rights law, and effective protection by the state could help combat land grabbing. Mozambique’s judiciary, civil society, and human rights institutions should work together to prevent local communities from being harmed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".