Sustainability Dimensions Assessment in Four Traditional Agricultural Systems in the Amazon
Bibliographic record
Abstract
Although traditional agriculture carried out by ethnic groups is considered for its high biodiversity and important for food security and sovereignty, few studies have investigated the potential of these systems in the interest of promoting a sustainable agricultural development policy according to United Nations Sustainable Development Goals. Using the FAO's Sustainability Assessment of Food and Agriculture (SAFA) methodology, this study analyzed the sustainability of four traditional agricultural systems, three indigenous (Waorani, Shuar, and Kichwa) and one migrant settler populations in the Yasuní Biosphere Reserve (YBR) and identified synergies and trade-offs among the dimensions of sustainability. The results showed different dynamics in all dimensions of sustainability-specifically, trade-offs in the dimensions of good governance with environmental integrity and social well-being, economic resilience, and social well-being. It was identified that the differences in terms of sustainability are narrowing between the indigenous Shuar people's traditional agricultural systems and those of migrant settlers, which provides policymakers with specific information to design sustainable development policies and rescue traditional agricultural systems in the Amazon region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".