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Record W3133260153 · doi:10.1080/02255189.2021.1892606

COVID-19 and crises of capitalism: intensifying inequalities and global responses

2021· article· fr· W3133260153 on OpenAlexvenueno aff
Sara Stevano, Tobias Franz, Yannis Dafermos, Elisa Van Waeyenberge

Bibliographic record

VenueCanadian Journal of Development Studies/Revue canadienne d études du développement · 2021
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCapitalismInequalityMateriality (auditing)Coronavirus disease 2019 (COVID-19)PandemicUnderpinningPoliticsPolitical scienceDevelopment economicsPolitical economy2019-20 coronavirus outbreakEconomic systemEconomic growthSociologyEconomicsBiologyVirology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has exposed multiple structural flaws of global capitalism. These have been reproduced through the intensification of inequalities and reinforced through policy responses that have failed to protect the most vulnerable from the health and socio-economic impacts of COVID-19. The COVID-19 pandemic has also revealed the materiality of human activity and complex geographies of inequality. It has highlighted how inequalities embedded in relations of production, reproduction and global finance continue to perpetuate the divide between the Global North and South. Using an interdisciplinary political economy lens with a focus on the Global South, this Special Issue brings together contributions that explore the dynamics underpinning the intensification of inequalities during the pandemic and that analyse the initial policy responses to the COVID-19 crisis.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.974
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0050.004
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.166
GPT teacher head0.301
Teacher spread0.135 · 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 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

Citations85
Published2021
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Development Studies/Revue canadienne d études du développementSame topicCOVID-19 Pandemic ImpactsFrench-language works237,207