The 2018 Municipal Elections in Jerusalem: A Tale of Fragmentation and Polarization
Bibliographic record
Abstract
This article analyzes the 2018 local elections in Jerusalem, the contested capital of the State of Israel. These elections were unique in terms of their level of competitiveness and fragmentation as well as producing a highly divided local government in the wake of the incumbent mayor’s, Nir Barkat’s, decision to leave the local political scene and enter national politics. While his party has no representation in city council, the new mayor of Jerusalem, Moshe Lion, built a broadly based new coalition that includes all parties in the council except for Hitorerut, the party that won the most seats and whose mayoral candidate, Ofer Berkovitch, was the runner-up to Lion. With the exception of the ultra-orthodox parties, national political parties that sought to interfere with the local electoral process to promote their candidates and lists by and large failed. Therefore, the governance of the city of Jerusalem once again fell under the control of the ultra-orthodox majority. Furthermore, even though the Arab population of East Jerusalem largely continued its traditional abstention from the electoral process, there was some evidence to suggest that a slight shift was taking place in that community in favor of participating in the institutional process of municipal government and democracy.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".