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Record W2768831782 · doi:10.1163/18763375-00903005

“Standoffish” Policy-making: Inaction and Change in the Lebanese Response to the Syrian Displacement Crisis

2017· article· en· W2768831782 on OpenAlexaff
Lama Mourad

Bibliographic record

VenueMiddle East Law and Governance · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRefugeeRefugee crisisState (computer science)Political scienceSyrian refugeesDevelopment economicsForced migrationGovernment (linguistics)AutonomyPopulationPolitical economyPer capitaEconomic growthLawSociologyEconomics

Abstract

fetched live from OpenAlex

With the largest refugee population per capita in the world, Lebanon now officially hosts at least 1.1 million Syrian refugees. Until late 2014, the Lebanese government maintained de facto open borders and little to no regulation of Syrians within its borders. This period has largely been understood as one of state absence: referred to broadly as a “policy of no-policy.” This paper looks at the way in which state inaction played a major role in structuring the responses that did emerge, both “below” and “above” the state, from local authorities and international agencies. I shed light on how indirect measures taken by the central government facilitated and encouraged greater local autonomy in governing the refugee presence. This, in turn, further decentralized and fragmented the current set of responses to the Syrian refugee crisis in Lebanon and legitimized discretionary action by municipal authorities.

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)0.013
metaresearch head score (Gemma)0.006
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 score0.024
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.018
Scholarly communication0.0110.003
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.053
GPT teacher head0.328
Teacher spread0.275 · 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

Citations53
Published2017
Admission routes1
Has abstractyes

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