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Record W2737916011 · doi:10.22215/cria.v3i0.122

Discovering the Palestinian Refugee Paradox in Lebanon

2016· article· en· W2737916011 on OpenAlexaffvenue
Carol Stephan

Bibliographic record

VenueCarleton Review of International Affairs · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsCarleton University
Fundersnot available
KeywordsRefugeePalestinian refugeesPalestinePolitical scienceComprehensive Plan of ActionLawHistoryAncient history

Abstract

fetched live from OpenAlex

This paper will attempt to analyze why Lebanon accepts so many refugees instead of initially denying them asylum since Lebanon’s refugee law reflects the country’s unwillingness to integrate refugees into its citizenry. It focuses on the case of Palestinian refugees in Lebanon and argues that Lebanon’s historical relations with Palestine and the Arab states, and its economic benefit from the refugees play a more powerful role than the country’s feeling of legal responsibility for granting these refugees asylum. The paper is divided into two sections; the first examines Lebanon’s refugee law and its consequences on the living conditions of refugees in Lebanon. The second section assesses the role of Arab nationalism and the economic benefit from refugees on influencing Lebanon to grant refugees asylum.

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)0.005
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.012
Scholarly communication0.0080.007
Open science0.0010.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.312
Teacher spread0.295 · 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
Published2016
Admission routes2
Has abstractyes

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