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Record W3022189539 · doi:10.20381/ruor-24720

An Island of Civility In an Ethos of Conflict: Examining Motivation, Constraint, and Social Change In Israeli-Palestinian Shared Society Peacebuilding

2020· dissertation· en· W3022189539 on OpenAlexfundno aff
Yoad Avitzur

Bibliographic record

VenueuO Research (University of Ottawa) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaWilfrid Laurier UniversityUniversity of Ottawa
KeywordsCivilityPeacebuildingEthosPolitical scienceConstraint (computer-aided design)Social changeSociologySocial psychologyPublic administrationLawPsychologyPoliticsEngineering

Abstract

fetched live from OpenAlex

This thesis studies an island of civility embedded in an ethos of conflict, focusing on a shared society peacebuilding initiative between Palestinian and Jewish citizens of Israel. Undertaken in close partnership with the NGO Hand in Hand: The Centre for Bilingual Jewish-Arab Education in Israel using a semi-participatory approach, this research describes the evolution of Hand in Hand from a small grassroots organization to a multimillion-dollar NGO. Drawing on survey data (n = 107), personal interviews (n = 25), and key insights from a four-month ethnography, this dissertation analyzes the social change function of Hand in Hand, ordinary citizens’ motivations for enrolling their children in bilingual (Hebrew/Arabic) schools, and the drivers and barriers for attending peacebuilding activities for adults.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.235
GPT teacher head0.398
Teacher spread0.163 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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