Defining “success” in large-scale agricultural investment: a typology based on different stakeholder perspectives
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In 2007/2008, a triple crisis of food, fuel and finance sparked a global rush for agricultural land; tens of millions of hectares were acquired, primarily by foreign investors, within countries in the Global South. Amidst those transactions, intergovernmental organizations, national governments, investors, and community members envisioned what “success” of such investments entails. Although not explicitly defined, each stakeholder had different conceptualizations and measures of it, based upon the descriptions used and desired outcomes sought. Despite a large amount of literature analyzing the global rush for land, as far as we are aware no one has analyzed the diverse viewpoints about what success entails. This paper compares conceptualizations among four key stakeholder groups, based on ideal types from dominant narratives, and develops a typology of ideal stakeholder framing of success to allow comparisons of uses and thereby provide a foundation for researchers who are assessing the global land rush. This paper provides clarity about widely used, but inconsistently defined, framing providing an important foundation for clarity of meaning and comparative differences between stakeholders. The typology advances the discourse on the land rush by providing nuance to this widely used framing and makes explicit its diverse meanings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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