MétaCan
Menu
Back to cohort
Record W1502669466 · doi:10.3386/w21341

Protecting Financial Stability in the Aftermath of World War I: The Federal Reserve Bank of Atlanta's Dissenting Policy

2015· report· en· W1502669466 on OpenAlexfundno aff
Eugene N. White

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
FundersYork UniversityNational Science Foundation
KeywordsAtlantaDissenting opinionPolitical scienceFinancial systemBusinessLawHistoryMetropolitan areaArchaeology

Abstract

fetched live from OpenAlex

During the 1920-1921 recession, the Federal Reserve Bank of Atlanta resisted the deflationary policy sanctioned by the Federal Reserve Board and pursued by other Reserve banks.By borrowing gold reserves from other Reserve banks, it facilitated a reallocation of liquidity to its district during the contraction.Viewing the collapse of the price of cotton, the dominant crop in the region, as a systemic shock to the Sixth District, the Atlanta Fed increased discounting and enabled capital infusions to aid its member banks.The Atlanta Fed believed that it had to limit bank failures to prevent a fire sale of cotton collateral that would precipitate a general panic.In this previously unknown episode, the Federal Reserve Board applied considerable pressure on the Atlanta Fed to adhere to its policy and follow a simple Bagehot-style rule.The Atlanta Fed was vindicated when the shock to cotton prices proved to be temporary, and the Board conceded that the Reserve Bank had intervened appropriately.

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)0.021
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.167
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0170.005
Open science0.0030.004
Research integrity0.0240.018
Insufficient payload (model declined to judge)0.0040.002

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 head0.306
GPT teacher head0.451
Teacher spread0.145 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNational Bureau of Economic ResearchSame topicBanking stability, regulation, efficiencyFrench-language works237,207