The Rush to the Peripheries: Land Rights and Tenure Security in Peri-Urban Ethiopia
Bibliographic record
Abstract
As the global population continues to urbanize, increasing pressure is put upon urban centers and the carrying capacity of the already built-up areas. One way to meet these demands is horizontal expansion, which requires new lands to become incorporated into urban centers. In most cases, this demand is met by converting peri-urban land into urban land as the urban center expands. These processes of expansion into the peri-urban, however, create tension regarding land use and land rights, and may foster tenure insecurity if not well managed. As in many countries, Ethiopia is experiencing extensive urban population growth and the peri-urban areas at the edge of urban centers are under pressure. This study investigates land rights issues and tenure security conditions of peri-urban farmers in the case study sites of Addis Ababa and Hawassa. The findings reveal that urban expansion into the peripheral agricultural lands and the resulting tenure system change has caused intense perceived tenure insecurity among peri-urban farmers. The range of land rights exercised differs in these two sites, as measured by the property rights analytical framework. Peri-urban farmers in Hawassa hold weak owner positions, enabling them to exercise thicker rights. However, peri-urban farmers in Addis Ababa hold weak claimant positions, which is slightly above the operational level right of an authorized user. This analysis suggests that the urban development and expansion strategies adopted by the respective city administrations are impacting land rights of the peri-urban farmers and their tenure security, albeit in unique ways, from which lessons can be drawn about how urban expansion policies can be more appropriately designed and implemented.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".