Bibliographic record
Abstract
The proposed paper looks at the Shab’a Farms - the linchpin excuse in the Hizb’Allah rhetoric justifying the destabilisation of the relationship Israel-Lebanon-Syria. It contemplates the possibility of defusing a violent conflict by borrowing the lease - a legal instrument in domestic law of contract and real property and private international law - and turning it into a public international legal device. The Shab’a (Shebaa) Farms, a tiny area located where Israel, Syria and Lebanon converge, is home to a geopolitical version of “Who’s on First?” It is arguably the most convoluted dispute over sovereignty and control in modern times, and has exasperated diplomats for decades. Israel captured the Shab’a Farms from Syria during the Six-Day War of 1967 and still occupies the area today. But Syria says the occupied land is Lebanese. Lebanon agrees – at least in official statements. Its political leaders are not all convinced; one recently said the Shab’a Farms belongs to Syria and that Israel’s occupation there isn’t Lebanon’s problem. Lebanon has proposed that the United Nations take charge of the area. But the United Nations has agreed with Israel’s claim that the territory is Syrian. Enter Hezbollah, which insists it is Lebanese, and this is what keeps returning the Shab’a Farms to regional prominence: the militant group regularly shells Israel’s forces there, claiming that Israel is illegally encroaching on Lebanese territory. The United States, the European Union, Egypt and others – all consider it necessary to resolve the Shab’a Farms conflict. As yet, none have had any success in pushing the parties toward a settlement. Amid this confused situation, there are two things the Shab’a Farms don’t have: inhabitants (they left), and a claim by the Palestinians. The absence of these potential obstacles to a solution might make the dispute over the area more amenable to resolution than other territorial conflicts in the region. Our paper, the first detailed work about the Shab’a Farms, will discuss how resolving this geographically small conflict can create the conditions for broader progress in regional peace talks. It will also propose to view the Shab’a Farms as a proto-type for the resolution of territorial conflicts by proposing a model of international trusteeship enabled by an international lease as a the legal instrument of conflict resolution.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".