Agricultural Land Use Change and its Drivers in the Palestinian Landscape Under Political Instability, the Case of Tulkarm City
Bibliographic record
Abstract
Agricultural land-use change is unavoidable with population growth and economic development. This study investigated the causes and the consequences of agricultural land-use change in Tulkarm city in the West Bank of Palestine after the construction of the Separation Wall. With the aid of GIS data, the study found that urban and built-up areas increased by 54% during the period 1999–2009. About 80% of the new urbanization occurred on agricultural land. Further, the study presented views of the urban planners, decision makers and farmers in Tulkarm regarding the main factors affecting agricultural land-use change in the city using qualitative interviews. The study found that the political factors, especially the existence of the Wall and the division of land into areas A, B and C, have had a major impact on the city’s uncontrolled development and the diffusion of urban areas on the landscape around the city. At the same time, unprofessional planning, lack of experience, and lack of communication and coordination between different planning organizations are considered major factors leading to uncontrolled and unorganized expansion of the city. Other factors such as farmers’ socio-economic status, land fragmentation, and population growth play essential roles in selling-off agricultural land for urban uses. Studying the dynamics of agricultural land-use change and the factors that led to this change in the West Bank in general, and in Tulkarm in particular, might help shape more robust theoretical understandings of how factors of land change interact under different circumstances, including protracted conflicts.
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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 | 0.001 | 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) | 0.000 | 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".