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Record W3098386305 · doi:10.1177/0956247820970094

COVID-19 responses: infrastructure inequality and privileged capacity to transform everyday life in South Africa

2020· article· en· W3098386305 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Urbanization · 2020
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsOvercrowdingSocial distanceEveryday lifeEconomic growthPovertyInequalityDevelopment economicsDistancingCoronavirus disease 2019 (COVID-19)Public healthPandemicPolitical scienceSocial isolationSociologyPsychologyEconomicsMedicine

Abstract

fetched live from OpenAlex

Throughout the early months of 2020, COVID-19 rapidly changed how the world functioned, with the closure of borders, schools and workplaces, national lockdowns, and the rapid normalization of “self-isolation” and “social distancing”. However, while public health recommendations were broadly universal, human capacity to accordingly transform everyday life has differed significantly. We use the example of South Africa to highlight the privileged nature of the ability to transform one’s life in response to COVID-19, arguing that the virus both highlights and exacerbates existing inequalities in access to infrastructure. For those living in urban poverty in South Africa, where access to basic infrastructure is limited, and where overcrowding and high density are the norm, it is frequently impossible to transform daily life in the required ways. The failure of global public health recommendations to recognize these inequalities, and to adapt advice to national and local contexts, reveals significant limitations that extend beyond this specific global pandemic.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.044
GPT teacher head0.274
Teacher spread0.230 · 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