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Record W2753442669 · doi:10.1080/09692290.2017.1355332

The international political economy of money, macro-money theories and methods

2017· article· en· W2753442669 on OpenAlexaff
Carla Norrlöf

Bibliographic record

VenueReview of International Political Economy · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomicsFinancial crisisPoliticsPositive economicsMacroeconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

The 2008 financial crisis exposed the fragility of advanced economies to financial caprice and the centrality of the United States in the global monetary order. Understanding the power structures behind global monetary orders, their distributional effects, as well as the systemic consequences associated with practices within domestic financial systems, particularly within financial centres, remains a priority. In a recent commentary, Cohen argues that the field is fragmented and that excessive attention to social scientific method is to blame. I agree with Cohen that the field of international political economy (IPE) of money is fragmented but I disagree that social scientific method is the cause. The fragmentation, and slow progress in the IPE of money, to which Cohen refers, is rather attributable to a lack of social scientific method, resulting in conceptual and empirical ambiguity, and unclear standards. Finally, I outline how social science methods could produce the kind of systemic analysis Cohen is calling for, ‘macro-money theories’, the flip side of the ‘micro-money theories’ embodied by open economy politics.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.343
Teacher spread0.317 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2017
Admission routes1
Has abstractyes

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