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Record W3016717403 · doi:10.1080/13549839.2020.1754375

The impossibility of social distancing among the urban poor: the case of an Indian slum in the times of COVID-19

2020· article· en· W3016717403 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

VenueLocal Environment · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsSocial distanceSlumPoliticsGovernment (linguistics)Metropolitan areaDistancingSociologyEconomic growthPolitical sciencePublic relationsCoronavirus disease 2019 (COVID-19)GeographyLawMedicineEconomicsPopulation

Abstract

fetched live from OpenAlex

As cases of COVID-19 were rising in India and the country’s political leadership instituted a nationwide lockdown, one of the authors of this article received a timely invitation from a friend – a government official – to make rounds with him and his team to various neighbourhoods within the metropolitan city of Bangalore. The team consisted of members working in healthcare, municipal corporation, and local police, and was tasked with ensuring that the government enacted measures of social distancing were being observed by local residents in public spaces. The author witnessed, in real time, the ways in which residents were engaging with the containment measures that were instituted as part of the political leadership’s attempt to flatten the curve of COVID-19. What was observed in an urban slum was particularly poignant and illuminating. The observations captured how, for residents of the urban slum, social distancing is more an aspiration than an attainable reality. Indeed, social distancing is impossible if such a protocol does not come with concomitant economic support targeted to the most socially vulnerable in society.

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)0.002
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 score0.323
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.239
Teacher spread0.215 · 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