Governance and security in Jerusalem the Jerusalem Old City Initiative
Bibliographic record
Abstract
Governance and Security in Jerusalem is the second in a series of three books which collectively present in detail the work of the Jerusalem Old City Initiative, or JOCI, a major Canadian-led Track Two diplomatic effort, undertaken between 2003 and 2014. The aim of the Initiative was to find sustainable governance solutions for the Old City of Jerusalem, arguably the most sensitive and intractable of the final status issues dividing Palestinians and Israelis. This book presents a collection of previously unpublished studies commissioned by the Initiative in aid of its work on the Special Regime. Split into three sections, the first part provides background papers on governance and security issues; the second presents Palestinian and Israeli partner perspectives on governance options for a special regime, and the third delivers partner perspectives on security studies for a special regime. The studies written by the Israeli and Palestinian partners provide important background and historical context for JOCI's work on security and governance. The position papers, presented in their original form, greatly influenced the development of the Special Regime governance model. Offering a unique insight on a range of governance and security issues in Jerusalem, this book will be of great significance to the policy-making community and students and scholars with an interest in Middle East politics, the Israeli-Palestinian conflict and the Middle East peace process
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".