Minding ‘Productive Gaps’: An Appraisal of Non-operational Land Deals in Seven Sub-Saharan African Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One of the dominant global development agendas for rural Africa in the past two decades has cast large-scale agro-industrial investments as a solution to achieve more efficient land use, higher crop yields, enhanced food security, and poverty reduction, among others. However, mounting evidence shows that this agenda has not fulfilled its promises: most land deals for agricultural production have not materialised as planned and their socio-economic development objectives often remain unreached. Despite the often severe impacts of non-operational projects, knowledge about why they fail to take place and operate remains fragmentary. Based on an extensive literature review of contemporary land deals in seven sub-Saharan countries, this paper sheds light on two ‘productive gaps’. First, the article delves into the ‘productive gap’ of land deals themselves, identifying key drivers of non-operational land deals. The reviewed literature points to local opposition and financial difficulties as significant factors impacting agricultural operations. Local opposition, in turn, stems largely from flawed land acquisition processes and unfulfilled investors’ promises. Second, this article offers a critical appraisal of the biases and oversights in the knowledge the land grab scholarship has ‘produced’.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it