Bibliographic record
Abstract
The dispute in Rand and Sembi v Serbia concerned land located near the Serbian capital’s airport, which was owned by foreign investors. The investors—Rand Investments Limited, William Archibald Rand, Kathleen Elizabeth Rand, Allison Ruth Rand, Robert Harry Leander Rand (the Rands) and Sembi Investment Limited (Sembi)—claimed that their rights as investors were compromised by a Serbian privatisation programme. Together they owned 75.87 percent of a farm of almost 300 hectares. The Canadian Rands relied on the Agreement between Canada and the Republic of Serbia for the Promotion and Protection of Investments,to file their claim for arbitration (Canada–Serbia BIT).3 Sembi, a Cypriot national, relied on the Agreement between Serbia and Montenegro and the Republic of Cyprus on the Reciprocal Promotion and Protection of Investments(Cyprus–Serbia BIT).4 Despite the different nationalities, the investors submitted a joint Request for Arbitration and based their claims on the same facts.5 This case comment...
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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 | 0.001 | 0.002 |
| 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".