Why are ecologically sensitive areas (ESAs) in African cities encroached on? Unveiling the encroachers' outlook
Bibliographic record
Abstract
Ecologically sensitive areas (ESAs) support the sustainability of cities worldwide. Nevertheless, their encroachment by grey land uses in cities, particularly in sub-Saharan Africa (SSA), has led to their sturdy deterioration. The current study assessed encroachers' appreciation of the utility of ESAs towards unpacking their motivation to encroach on these spaces. This has received limited scholarly attention. The study empirically focused on Kumasi, a rapidly urbanising city in Ghana, and adopted the convergent parallel mixed-method design to gather and analyse data. The results indicate that the encroachment phenomenon is not monolithic. Generally, encroachers were more aware of ESAs' provisioning and cultural functions than their regulating and ecosystem services. The results further revealed that urbanisation, the dual system of urban land management, and individuals' ignorance of the importance of ESAs were the main factors that contributed to the overall depletion of ESAs. The study found evidence of both ‘ bold ’ and ‘ quiet ’ encroachment where, on the one hand, some actors (particularly property developers) courageously encroached and consolidated their gains via political maneuvers, while on the other hand, ‘ordinary’ individuals incrementally and silently encroached due to limited housing and economical options. The paper concludes by recommending that policies and regulations designed to manage ESAs should move away from a brutal and violent enforcement approach to critically consider the perspective of encroachers. One critical strategy is to educate encroachers to enhance both their awareness and knowledge of the importance of ESAs. • The article assesses encroachers’ appreciation of the utility of ESAs and their motivation to encroach on them. • Urbanization, dual urban land management, and individuals’ ignorance contribute to the depletion of ESAs. • Instances of both bold and quiet encroachment were identified. • Encroachment could be minimized by raising awareness and knowledge levels of the importance of ESAs.
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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 | 0.000 | 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) | 0.001 | 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".