Land tenure (in) security in the context of urban flood risk in Ghana
Bibliographic record
Abstract
The increasing incidence of floods driven by urbanization and climate change destabilizes urban social, economic and environmental systems where land tenure is integral. Land tenure security is regarded as an essential element in navigating adaptations to disaster events, including floods. However, the occurrence of floods itself could be a source of land tenure insecurity. This study, drawing on political ecology and the diverse theoretical framings of tenure security, examines the impacts of floods on the land tenure security of flood victims. Through semi-structured interviews with flood victims and planning officials, the findings show that flooding-induced rezoning and the development of new planning schemes, tenant insecurity, relocation, loss of land documents, and threats to urban agriculture affect the land tenure security of flood victims. We identified that the possession of land documents is essential to tenure security, but not an absolute condition for the perceived tenure security of flood victims. The findings show that flood risk management through post-flood land use planning has the potential to have dual impacts on community resilience and tenure security. On the one hand, it can enhance tenure security and bolster community resilience. On the other hand, when executed in an exclusionary manner that overlooks the urban poor, it has the potential to perpetuate inequalities and tenure insecurity. We recommend tenure-responsive land use planning and embedding contextual, procedural, and distributive equity principles in land use planning responses to urban floods to safeguard the tenure security of the most vulnerable populations. • Land tenure security is essential in navigating adaptations to disaster events. • Tenant insecurity and threat to urban agriculture obstruct economic tenure insecurity. • Loss of land documents through floods impede formal and legal tenure security. • Post-flood land use planning has the potential to have dual impacts on resilience and tenure security. • Tenure-responsive land use planning and equity tenets should inform Planning responses to urban floods.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".