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Record W4284970804 · doi:10.5281/zenodo.6814020

Draft analysis of how networks of international, national and local actors collaborate to reduce vulnerabilities on Six Sites in Europe, Canada, and South Africa

2022· report· en· W4284970804 on OpenAlexaboutno aff
Christine Jacobsen, Marry-Anne Karlsen, Jo Vearey

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typereport
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsGeographyPolitical scienceRegional scienceEnvironmental protectionEnvironmental resource managementEnvironmental planningEnvironmental science

Abstract

fetched live from OpenAlex

Based on fieldwork conducted in selected migration arrival ports in Greece, Italy, Spain, France, South Africa, and Canada, this research report explores the role of the notion of vulnerability in the field level governance of international protection. Specifically, it explores how key actors and stakeholders in the selected field sites 1) understand and apply the notion of vulnerability, and 2) collaborate to address and reduce vulnerabilities. Particular attention is paid to how field level governance takes into account gender and legal status, and how actors collaborate in regard to mechanisms for identification, access to legal information and assistance, and access to healthcare and shelter. The field level is where global, regional, national and local actors and stakeholders interact in order to implement the international protection regime. A great variety of actors and stakeholders are as such engaged in the field level governance of migration and refugee protection, including notably government agencies, local authorities, civil society organizations, host community members, and migrants. Critically, our research provides opportunities to explore de facto governance responses and how they do or do not reflect formal governance processes - including national legislative frameworks and the global compacts on refugees and migration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.285
Teacher spread0.240 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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