MétaCan
Menu
Back to cohort
Record W2601102644 · doi:10.25071/1920-7336.40451

Finding Space for Protection: An Inside Account of the Evolution of UNHCR’s Urban Refugee Policy

2017· article· en· W2601102644 on OpenAlexvenueno aff
Jeff Crisp

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeePolitical sciencePerspective (graphical)Public administrationUrban policyProcess (computing)Space (punctuation)Domain (mathematical analysis)Urban planningLawComputer scienceEngineering

Abstract

fetched live from OpenAlex

This article examines the evolution of UNHCR’s urban refugee policy from the mid-1990s to the present. It focuses on the complex and contested nature of the policymaking process, analyzing the roles that internal and external stakeholders have played in it. At the same time, the article identifies and examines key developments in UNHCR’s operational environment that drove and constrained policymaking in this domain. The article is written from the perspective of a former UNHCR staff member who was substantively engaged in urban refugee policy.

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)0.012
metaresearch head score (Gemma)0.011
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: none
Teacher disagreement score0.124
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0160.028
Scholarly communication0.0150.009
Open science0.0020.013
Research integrity0.0050.008
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 head0.026
GPT teacher head0.317
Teacher spread0.291 · 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

Citations35
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueRefuge Canada s Journal on RefugeSame topicGlobal Peace and Security DynamicsFrench-language works237,207