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Record W3212177144 · doi:10.21203/rs.3.rs-1029118/v1

The National and Global Impact of Systemic and Structural Violence on the Effective Prevention, Treatment and Management of COVID-19 in the African/Black Population: a Scoping Review Protocol

2021· review· en· W3212177144 on OpenAlexafffundabout
Roberta Timothy, Robert Chin-see, Julia Martyniuk, Pascal Djiadeu

Bibliographic record

VenueResearch Square · 2021
Typereview
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsImpactWilfrid Laurier UniversityMcMaster UniversityUniversity of Toronto
FundersUniversity of Toronto
KeywordsCoronavirus disease 2019 (COVID-19)Protocol (science)PopulationMedicineEnvironmental healthAlternative medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background: As the SARS-CoV-2 virus continues to ravage the globe and cases exploded rapidly, countries have been presented with challenging policy choices to contain the spread of COVID-19. In Canada, and globally, the COVID-19 pandemic has added a new stratum to the debate concerning the root causes of global and racial health inequities and disparities. Individuals who exist as targets of systemic inequities are not only more susceptible to contracting COVID-19, but they are also more likely to bear the greatest extent of the subsequent economic pandemic. Therefore, data collection that specifically focuses on the impact of COVID-19 on the lives and health of African/Black communities nationally and globally is needed to develop intersectional, culturally-relative, anti-racist/anti-oppression, empowerment-centered interventions and social policies to increase more efficient ways to support heterogeneous African/Black communities during and after the COVID-19 pandemic.The primary objective of this review is to investigate the impact and management of COVID-19 on African/Black individuals and communities in Canada and globally and understand how anti-black racism and intersectional violence impact the health of African/Black communities during the COVID-19 pandemic.Methods and analysis: A systematic search of published literature of quantitative and qualitative studies published on COVID-19 in Canada and globally will be conducted in Ovid Medline, Ovid EMBASE, EBSCO Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, Ovid PsychInfo, Ovid CAB Abstracts, Scopus, Web of Science, and Global Index Medicus.To be included in the review, studies should include data on COVID-19 in relation to African/Black individuals, population and communities in Canada and globally. The studies must discuss racism, oppression, anti-oppression, or systemic/structural violence and be published in English, French, Spanish, and Portuguese. The findings will be reported according to PRISMA-ScR.Conclusion: This review will collect important data and evidence on African/Black communities related to COVID-19. Moreover, this review could help identified existing gaps in COVID-19 management in the African/Black communities and inform future research. Furthermore, it could also be used in decision-making for health policy and promotion and can influence the services provided by healthcare facilities and community organizations around the globe. Systematic Review registrations: Open Science Framework (OSF). Submitted on November 1st, 2021.

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)0.065
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.065
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.088
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0210.018
Science and technology studies0.0040.004
Scholarly communication0.0080.006
Open science0.0050.006
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0390.005

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 head0.157
GPT teacher head0.583
Teacher spread0.426 · 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 designSystematic review
Domainnot available
GenreProtocol

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
Published2021
Admission routes3
Has abstractyes

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