Jordan Valley Under Israeli Ihtilal: A Palestinian Story of Stark Oppression
Bibliographic record
Abstract
The Jordan Valley of Palestine is a site of poverty and targeting of a population, subjecting the native Palestinian inhabitants to sub-standard living conditions worse than any other areas in the West Bank under Israeli military occupation for more than half a century. Taking a grounded theory approach, this paper aims at presenting the voices of marginalized ordinary Palestinian locals, to be heard and reflected upon within a critical analytical geography context. For its part, Israel’s strategies of occupation and colonizing are geared towards controlling and fencing in over 90 percent of the Jordan Valley’s land, and by extension securing its resources (i.e., water, fertile agricultural and pastureland) for the benefit of the incoming Jewish settlers, now numbering some 10 000. This is at the expense of the indigenous 60 000 Palestinians, whose daily lives are marked by a severe lack of the adequate basics in health, access to education and other facilities, let alone minimum human rights. The paper details the daily life of Palestinians in the Occupied Jordan Valley, embedded within a system of oppressive actions and suffering inflicted on a population by a state prioritizing one minority ethnic group in the area over its natives. A critical geographic lens reveals the stark details of the Jordan Valley’s Palestinian social and spatial reality.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.034 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| 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".