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Record W2071185724 · doi:10.1177/0010414006290109

Religious—Nationalist Mobilization and State Penetration

2007· article· en· W2071185724 on OpenAlexaff
Oded Haklai

Bibliographic record

VenueComparative Political Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsHuman settlementMobilizationFacilitatorState (computer science)Political scienceBureaucracyEnforcementNationalismPublic administrationPolitical economyLawLaw and economicsSociologyPoliticsEngineering

Abstract

fetched live from OpenAlex

When will public agencies act in violation of the rules set by the state in a strong state? This article demonstrates that when an organized religious— nationalist force manages to penetrate the state apparatus, it can cause the state to lose some enforcement capacity vis-à-vis the penetrating force. The activists, in turn, can use the infiltrated arms of the state to realize their preferences, even if the pursuant practices contradict state laws. These conclusions are based on research conducted on Jewish settlements constructed unlawfully in the West Bank. The establishment of these settlements necessitated some collaboration from state agencies. Settler activism that included penetration into important arms of the bureaucracy is identified as an important facilitator of unauthorized settlements. The lessons drawn from the case are generalizable and can apply to other types of societal mobilization.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0040.002
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.142
GPT teacher head0.436
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), 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

Citations40
Published2007
Admission routes1
Has abstractyes

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