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Record W4225159018 · doi:10.25071/1920-7336.40874

Solidarity in the Time of COVID-19: Refugee Experiences in Brazil

2022· article· en· W4225159018 on OpenAlexfundvenueno aff
Patrícia Nabuco Martuscelli

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2022
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersUniversity of Ottawa
KeywordsSolidarityRefugeeNarrativePandemicCoronavirus disease 2019 (COVID-19)Gender studiesPolitical scienceSociologyConsciousnessPopulationMedicinePsychologyDemographyLawPolitics

Abstract

fetched live from OpenAlex

Refugees have adopted solidarity actions during the COVID-19 pandemic, even after being left behind during health emergencies. This article contributes to the literature on solidarity and asylum by discussing refugees’ solidarity narratives towards vulnerable Brazilian groups, the refugee community, and the Brazilian population in general. The author conducted 29 in-depth semi-structured interviews with refugees living in Brazil between March 27 and April 6, 2020. Refugees’ past suffering experiences make them more empathic to other people’s suffering due to the pandemic, which creates an inclusive victim consciousness that seems to explain their solidarity narratives towards different groups.

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)0.004
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.011
Scholarly communication0.0050.004
Open science0.0010.010
Research integrity0.0020.003
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 head0.023
GPT teacher head0.338
Teacher spread0.316 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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