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Record W4231398404 · doi:10.1525/jps.2016.46.1.s1

Settlement Monitor

2016· article· en· W4231398404 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Palestine Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)Quarter (Canadian coin)West bankState (computer science)HistoryPrime ministerPresidential systemArchaeologyLawPolitical sciencePalestineAncient historyPoliticsPaymentBusiness

Abstract

fetched live from OpenAlex

AbstractThe Settlement Monitor covers items—reprinted articles, statistics, and maps—pertaining to Israeli settlement activity in the West Bank, East Jerusalem, and the Golan Heights. They are reproduced as published, including original spelling and stylistic idiosyncrasies. Significant developments this quarter: As the first half of 2016 came to a close, Israel continued demolishing Palestinian homes in Area C of the West Bank and stepped up punitive and agenda-driven demolitions across East Jerusalem. Israeli prime minister Benjamin Netanyahu also approved 800 new settlement units and announced another 600 in Beit Safafa after a spate of violent attacks in June and July. While officials in the United States were preoccupied with upcoming presidential elections, the Jerusalem Municipal Council for Planning and Building pushed forward with stalled expansion plans for the Ramot settlement, while Israel declared an area south of Bethlehem as state land to expand the Gush Etzion settlement bloc. Finally, Israel attempted to appease its settlers further by exploring means to override the High Court's decision to evacuate the illegal Amona outpost.AmonaSilwanBeit SafafaArea CWest BankEast Jerusalemhome demolitions

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.178

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.372
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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