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Record W4317787971 · doi:10.1215/00182702-10956544

Six Decades of Economic Research at the Bank of England

2023· article· en· W4317787971 on OpenAlexaff
Juan Acosta, Béatrice Cherrier, François Claveau, Clément Fontan, Aurélien Goutsmedt, Francesco Sergi

Bibliographic record

VenueHistory of Political Economy · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversité de Sherbrooke
FundersEconomic and Social Research CouncilNew York University Abu Dhabi
KeywordsCitationCommercial bankChinese financial systemEconomyPolitical scienceEconomicsRegional scienceSociologyFinanceLawChina

Abstract

fetched live from OpenAlex

Abstract This paper discusses the transformation of the content, role, and status of economic research at the Bank of England in the past sixty years. We show how three factors (the policy functions and missions of the Bank, the attitude of its executives toward economics, and its organizational structure) shaped the evolution of in-house economic research at the Bank during three distinctive periods (1960–91; 1992–2007; 2007–14). Our account relies on a broad set of sources and methods (the Bank's publications, archives, interviews with current and former Bank economists, citation analysis, prosopography, and topic modeling).

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)0.012
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0140.021
Science and technology studies0.0020.006
Scholarly communication0.0110.006
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.202
GPT teacher head0.312
Teacher spread0.110 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations21
Published2023
Admission routes1
Has abstractyes

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