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Record W7071865918

Towards a reception system that recognizes, addresses and reduces the situations of vulnerability of asylum seekers and refugees in Italy

2023· other· en· W7071865918 on OpenAlexaboutno aff

Bibliographic record

VenueARCA (Università Ca' Foscari Venezia) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodHyporeflexiaProteogenomicsDiafiltrationTSG101TubulopathyArticular cartilage damage
DOInot available

Abstract

fetched live from OpenAlex

The VULNER project conducted an extensive inquiry in eight countries – in Europe (Belgium, Germany, Italy, and Norway), the Middle-East (Lebanon), Africa (Uganda and South Africa), and North America (Canada). The inquiry thus covered a variety of policy contexts, ranging from humanitarian responses in first countries of asylum (Lebanon and Uganda) to asylum and other related processes addressing the protection needs of migrants in Western countries (Belgium, Germany, Italy, and Norway). The objective was to gain a better understanding of the multiple challenges, promises, and pitfalls of relying on ‘vulnerability’ as a conceptual tool to design and implement institutional responses to migrants’ protection needs. Based on the results of the second research phase (2021-2022) in Italy, this policy brief proposes concrete policy recommendations on how to design migration and asylum policies in Italy, which effectively consider and address the vulnerabilities among refugees, asylum seekers, and migrants.

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)0.008
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.031
GPT teacher head0.269
Teacher spread0.238 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueARCA (Università Ca' Foscari Venezia)French-language works237,207