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Record W4285802733 · doi:10.1080/09692290.2022.2097289

A critical analysis of international organizations’ and global management consulting firms’ consensus around twenty-first century skills

2022· article· en· W4285802733 on OpenAlexafffund
Linda A. White, Sumayya Saleem, Elizabeth Dhuey, Michal Perlman

Bibliographic record

VenueReview of International Political Economy · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitationCommissionUnderpinningSociologyPolitical sciencePublic relationsAccountingEconomicsLaw

Abstract

fetched live from OpenAlex

A growing number of academic studies and policy reports have identified a set of core skills considered crucial in the twenty-first century economy. This article critically examines the evidence base underpinning that ideational consensus among international organizations (IOs) and global management consulting firms (GMCFs). We collected 234 skills reports produced over the past decade by major IOs (European Commission, ILO, OECD, UNESCO, and World Bank) and GMCFs (BCG, Deloitte, Ernest and Young, KPMG, McKinsey, and PWC). We then extracted bibliographic references from each report and used the analytic technique of citation analysis to examine how the consensus around these core skills was generated in order to uncover the authoritative sources of knowledge and the pattern of ideational policy diffusion observed. Our analysis reveals substantial gaps in the evidence base used. Evidence drew largely on a few academic economists, along with strong use of grey literature, and high rates of self-citation. Given these characteristics, the consensus around twenty-first century skills appears less epistemic in nature and more like an ideational echo chamber, which raises concerns about the extent to which policymakers should rely on this evidence.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.267
Teacher spread0.259 · 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.

Study designTheoretical or conceptual
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

Citations12
Published2022
Admission routes2
Has abstractyes

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