Reviewing the Interactions between Conflict and Demographic Trends in the Occupied Palestinian Territories: The Case of The Gaza Strip
Bibliographic record
Abstract
This paper reviews the interactions between conflict and demographic trends in the Occupied Palestinian Territories (OPT), and provides an analysis of The Gaza Strip. Palestinian society has experienced momentous demographic transition over the past century, as well as recurrent waves of displacement and outbreaks of conflict and violence over the last decade. The enclave has witnessed demographic changes, with the emergence and rule of Hamas, repeated wars, and, since 2007, the unlawful blockade of The Gaza Strip. The United Nations (UN) has warned that, living conditions in Gaza are deteriorating faster than forecast, and are predicted to become dire by 2020. This paper provides a brief review of theories linking conflict and demography, followed by an introduction to the historical and contemporary context of The Gaza Strip. An in-depth analysis of the impact that conflict has on the demographic structure of Palestinian society in The Gaza Strip, focusing on the factors behind high fertility rates, population growth trends, and the drivers of migration. The analysis offered builds upon interviews with Palestinian experts, and Palestinian asylum-seekers in Greece, Poland, U.K. and Sweden, in addition to data published by the Palestinian Statistics Bureau Centre and research articles focusing on The Gaza Strip. The paper concludes that, the Palestinian reconciliation agreement should take priority over the population and the economy.
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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 | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".