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Record W4408999293 · doi:10.1017/asr.2025.20

Decentering the Dollar in Africa-China Trade: How Nigerian Entrepreneurs Navigate Currency Swaps and Digital Currencies in an Era of USD Hegemony and RMB Internationalization

2025· article· en· W4408999293 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAfrican Studies Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Global Influence and Migration
Canadian institutionsMacEwan University
FundersSocial Sciences and Humanities Research Council of CanadaMacEwan UniversityWenner-Gren Foundation
KeywordsRenminbiHegemonyInternationalizationCurrencyLiberian dollarChinaUs dollarEconomicsBusinessInternational tradeInternational economicsCommercePolitical scienceMonetary economicsFinance

Abstract

fetched live from OpenAlex

Abstract Debates on dedollarizing and internationalizing China’s currency, the renminbi (RMB), often focus on state-led initiatives such as bilateral currency swaps and Central Bank Digital Currencies while overlooking the role of entrepreneurs utilizing US dollar (USD) alternatives. Ethnographic fieldwork with Nigerian importers of Chinese goods reveals how parallel payment currencies and channels—informal naira-RMB transfers and illicit cryptocurrency transactions—are just as essential in the Global South to decenter US dominance: its currency, institutions, and authority. Analyzing formal monetary policies and local money practices, Liu shows how Nigerian importers cultivate multicurrency fluency, which is vital in an incipient era of political and economic multipolarity.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.348

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 science0.0000.000
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 head0.036
GPT teacher head0.351
Teacher spread0.315 · 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