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Record W3132683279 · doi:10.7202/1075119ar

WHEN TWO PANDEMICS COLLIDE: RACISM, COVID-19 AND THE ASSOCIATION OF BLACK SOCIAL WORKERS EMERGENCY RESPONSE

2021· article· en· W3132683279 on OpenAlexvenueaboutno aff
Wanda Thomas Bernard

Bibliographic record

VenueCanadian social work review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsRacismPandemicContext (archaeology)Government (linguistics)Political scienceSocial workPublic relationsSociologyCoronavirus disease 2019 (COVID-19)MedicineGender studiesGeography

Abstract

fetched live from OpenAlex

In the spring of 2020, African Nova Scotians were faced with two emerging pandemics: the ongoing pandemic of anti-Black racism, and the pandemic of COVID-19. The Association of Black Social Workers created a response specific to the needs of African Nova Scotians, employing the six practice principles of Africentric social work. They established a partnership with community and government partners to manage a phone line to triage based on need, and a virtual community check-in to connect about the pressing Black Lives Matter movement. This paper contextualizes the historic and current systemic racial inequities faced by African Nova Scotians within the context of the current public health emergency, and the need for an equitable, community-based emergency response. This specialized, Africentric service provision model can be used to inform the development of emergency responses for other Black communities in Canada.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.136
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.005
Scholarly communication0.0040.001
Open science0.0010.002
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 head0.055
GPT teacher head0.389
Teacher spread0.334 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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