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Record W7034141590

Syrian Migration Crisis (Refugees Protection and Implementation of a Safe Resettlement Programs/Visa Programs to Reduce Illegal Immigration)

2021· dissertation· en· W7034141590 on OpenAlexaboutno aff

Bibliographic record

VenueE-resource repository of the University of Latvia (University of Latvia) · 2021
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsSyrian refugeesRefugee crisisRefugeeHumanitarian crisisImmigrationConventionHuman rightsIllegal immigrants
DOInot available

Abstract

fetched live from OpenAlex

Syrian refugees’ crisis is one of the major and prolonged refugee crises since WWII; millions of Syrian citizens were displaced and migrated as a result of the war in Syria. The migration flow of Syrian people is continuously occurring towards Europe and neighboring countries of Syria, and, to date, the crisis remains still unsolved. 2021 marked the tenth anniversary since the starting point of the Syrian war, but, a decade later, the international community’s response toward the crisis has not yet resolved the facets of the Syrian immigration crisis. The flow of Syrian migrants toward Europe is expected to sharply increase after lifting COVID-19 restrictions. European countries have to promote resettlement programs and visa programs for Syrian migrants in order to encourage a legal method of migration. Following an analysis of the background of the Syrian immigration crisis, the distribution of Syrian migrants in neighboring countries of Syria, and the rights of refugees under the 1951 Convention relating to the status of refugees and its Protocol, this Thesis addresses the humanitarian visa and resettlement programs of the European Union, especially focusing on the case-studies of Belgium and Canada and their programs for Syrian migrants. Then the Thesis provides an analysis of the case-law relating to the humanitarian visa of Syrian migrants in the two different European courts, the Court of Justice of the EU and the European Court of human rights.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.034

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 studies0.0040.002
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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