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Record W3094272394 · doi:10.3138/jcfs.51.3-4.012

COVID-19 in Ghana: Changes and the Way Forward

2020· article· en· W3094272394 on OpenAlexvenueno aff
Joana Salifu Yendork, Spencer James

Bibliographic record

VenueJournal of Comparative Family Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicEconomic growthGovernment (linguistics)Empirical evidenceMiddle classEthnic groupMental healthDistribution (mathematics)BusinessDevelopment economicsPolitical scienceEconomicsCoronavirus disease 2019 (COVID-19)PsychologyMedicine

Abstract

fetched live from OpenAlex

As a lower-middle income country, Ghana is noted for having a progressive economy, health system, and family trends. However, COVID-19, with it associated restrictions, has brought changes to various aspects of Ghanaians’ lives. In this paper, we review information from government websites, online media websites, social media, academic articles, and anecdotal evidence to track changes brought about by the pandemic. Specifically, we focus on economic well-being, education and schooling, family interaction, mental health and communication in community as well ethnic, cultural, and social class variations. Findings show that the COVID-19 pandemic is changing life for all Ghanaians, notably by reinforcing existing inequalities and highlighting previously known gaps in service, coverage, and access across multiple sectors, including healthcare, business and education. Family patterns are changing for both the nuclear and extended family units. The pandemic has created both challenges and opportunities for parents to engage with their children. Anxiety levels are heightened and psychological services have consequently been made widely available. Education has slowly and unevenly gone virtual. Further, the crisis has generated local innovations to meet the nation’s needs during the pandemic. The findings call for national reforms in the production and distribution of goods and services in all sectors as well as empirical work into the long-term effects of the pandemic on Ghanaians.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.247
GPT teacher head0.360
Teacher spread0.114 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations14
Published2020
Admission routes1
Has abstractyes

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