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Record W4310370903 · doi:10.1177/00208728221137531

Whose life matters? A call for social work action in response to a global humanitarian crisis

2022· article· en· W4310370903 on OpenAlexaffabout
Marjorie Johnstone, Eunjung Lee, Emel Seven Bozcam

Bibliographic record

VenueInternational Social Work · 2022
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsWilfrid Laurier UniversityUniversity of TorontoDalhousie University
Fundersnot available
KeywordsSolidarityRefugeeFace (sociological concept)Social workPolitical scienceAction (physics)Work (physics)Spanish Civil WarHumanitarian crisisHuman rightsCivil societyPolitical economySociologyLawSocial science

Abstract

fetched live from OpenAlex

In a few short weeks, the war in Ukraine displaced over four million people. As a human rights profession in the new global order, the social work profession has called for not only the support of social workers in Ukraine and their neighboring countries but also for pressure on all host countries to facilitate fast, efficient admission of asylum seekers and strengthening of resettlement services. Using Canada as a case study, we identify barriers that became apparent during the Syrian civil war and suggest ways all social workers can act in solidarity in the face of this global travesty.

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)0.016
metaresearch head score (Gemma)0.022
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0410.036
Scholarly communication0.0180.013
Open science0.0030.014
Research integrity0.0140.029
Insufficient payload (model declined to judge)0.0060.001

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 head0.052
GPT teacher head0.396
Teacher spread0.345 · 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
GenreCommentary

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

Citations3
Published2022
Admission routes2
Has abstractyes

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