MétaCan
Menu
Back to cohort

The Office of the United Nations High Commissioner for Refugees

2021· book-chapter· en· W3173521534 on OpenAlexaff
James Milner, Jay Ramasubramanyam

Bibliographic record

VenueOxford University Press eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsCarleton University
Fundersnot available
KeywordsRefugeeMandateStatutePolitical scienceScope (computer science)ConventionRefugee lawLawInternational lawPublic administrationComputer science

Abstract

fetched live from OpenAlex

Abstract This chapter addresses the role played by the Office of the United Nations High Commissioner for Refugees (UNHCR) in the making and implementation of international refugee law. It begins by considering UNHCR’s mandate responsibilities and operational functions to better understand the structures that condition the scope of UNHCR’s engagement with the functioning of international law. While UNHCR’s 1950 Statute and the Refugee Convention both mandate UNHCR to serve particular functions, such as its supervisory responsibility relating to the Refugee Convention, its Statute also places particular constraints on UNHCR, especially in terms of the scope of its activities and its reliance on voluntary contributions from States to perform its mandated functions. The chapter then looks at how the roles UNHCR has played in the making and implementation of refugee law at the global, regional, and national levels, through its operations, and how these functions have evolved over time. By illustrating the various instances where UNHCR has demonstrated power, along with those instances where UNHCR has exhibited pathologies and has been constrained by the interests of States, the chapter points to the importance of understanding international refugee law within the political environment in which it functions.

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0480.013

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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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
GenreOther

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

Citations34
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicMigration, Refugees, and IntegrationFrench-language works237,207