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Record W2694563292 · doi:10.1080/10670564.2017.1337291

Domestic Politics and External Financial Liberalization in China: The Capacity and Fragility of External Market Pressure

2017· article· en· W2694563292 on OpenAlexaff
Doménico Lombardi, Anton Malkin

Bibliographic record

VenueJournal of Contemporary China · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsFragilityPoliticsLiberalizationChinaFinancial fragilityEconomicsInternational economicsFinancial systemMarket economyBusinessEconomic systemPolitical scienceFinancial crisisMacroeconomicsLaw

Abstract

fetched live from OpenAlex

This article explores how the Chinese Communist Party has relied in part on making global financial markets and institutions a source of external pressure to help pass domestic economic and financial reform. We explore two case studies of external financial liberalization: the listing of Chinese state-owned enterprises on foreign stock exchanges and the financial reform aspects of the Shanghai Free Trade Zone. These studies show that external liberalization policies are interlinked with both micro- and macro-level reforms in the domestic economy. We conclude that, after 2005, this strategy of applying external pressure, in fact, did not lead to more comprehensive economic restructuring because the agents of external pressure—in this instance, foreign banks and accounting firms—were themselves party to the reinforcement of state control and ultimately did not (or could not) promote further external liberalization. Domestic agents that supported external liberalization were also quick to abandon it when external pressure conflicted with other domestic policy objectives.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.015
GPT teacher head0.276
Teacher spread0.261 · 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 designObservational
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

Citations8
Published2017
Admission routes1
Has abstractyes

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