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Record W2209281509 · doi:10.1017/s2044251315000211

Barriers to Ratification of the United Nations Protocol Against the Smuggling of Migrants

2015· article· en· W2209281509 on OpenAlexaboutno aff
Andreas Schloenhardt, Hamish Macdonald

Bibliographic record

VenueAsian Journal of International Law · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
FundersUtah Agricultural Experiment Station
KeywordsRatificationProtocol (science)IncentiveInternational tradeOrder (exchange)Montreal ProtocolPolitical scienceComputer securityBusinessGeographyLawEconomicsComputer scienceMedicinePoliticsFinance

Abstract

fetched live from OpenAlex

Abstract The United Nations Protocol Against the Smuggling of Migrants by Land, Sea and Air sets out an ambitious international approach to prevent and combat the smuggling of migrants. Although the Protocol has found widespread adoption worldwide, many countries have not—or not yet—signed and ratified the Protocol. Many critics argue that the Protocol promotes the views of rich, developed destination countries and offers little incentives for developing countries of origin to support the Protocol. This paper examines the reasons why some countries choose not to ratify the Protocol. The paper sheds light on the common concerns and characteristics of the forty-five non-Party States in order to pave the way for wider adoption of the Protocol and for more concerted efforts to combat the smuggling of migrants worldwide.

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)0.093
metaresearch head score (Gemma)0.109
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 score0.093
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0930.109
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0090.009
Scholarly communication0.0090.004
Open science0.0020.008
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0050.001

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 head0.033
GPT teacher head0.336
Teacher spread0.302 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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