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Record W3104515032 · doi:10.1080/02255189.2020.1839394

Never let a pandemic go to waste: turbocharging the private sector for development at the World Bank

2020· article· en· W3104515032 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Development Studies/Revue canadienne d études du développement · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsPrivate sectorCorporationPublic sectorBusinessFinancial institutionInstitutionPrivate finance initiativeFocus groupPandemicEconomic growthEconomic policyFinancePublic administrationPolitical scienceCoronavirus disease 2019 (COVID-19)EconomicsEconomyMarketing

Abstract

fetched live from OpenAlex

This article scrutinises the first four months of the World Bank Group’s Covid-19 response and reveals a persistent prioritisation of private over public interests. The Group’s private sector arm, the International Finance Corporation, and its financial sector clients, have prevailed in terms of emergency resource allocations. And, while support from the Group’s public sector arms has been portrayed as aiming to strengthen public systems, recipient countries have been urged not to forego structural reforms in support of the private sector. This includes an enhanced focus on public–private partnerships to deliver ostensibly public services. The institution has seized the current crisis as an opportunity to intensify its “Maximising Finance for Development” approach.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
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 head0.097
GPT teacher head0.286
Teacher spread0.188 · 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