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Record W4206980860 · doi:10.1177/00208728211070525

The role of social work in the healthcare settings during the COVID-19 pandemic in Africa

2022· article· en· W4206980860 on OpenAlexaff
Richard Baffo Kodom

Bibliographic record

VenueInternational Social Work · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPandemicLaggingHealth careWork (physics)Coronavirus disease 2019 (COVID-19)Social workHealthcare deliveryPublic relationsPolitical scienceMedicineEconomic growthEconomicsEngineering

Abstract

fetched live from OpenAlex

Globally, the social work profession seeks to empower and support vulnerable groups during the COVID-19 pandemic. These roles and responsibilities seem to be lagging in Africa as the potentials of social workers are underutilized in many areas of practice including the hospital setting. Given the contributions of medical social work, this article highlights the roles of social workers in healthcare delivery amid the COVID-19 pandemic. In addition, it emphasizes the challenges of medical social work. Since healthcare delivery requires collaboration, suggestions are made regarding ways to incorporate medical social work in healthcare settings for optimal healthcare delivery.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0110.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.386
Teacher spread0.340 · 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 teacher head, not a consensus.

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

Citations10
Published2022
Admission routes1
Has abstractyes

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