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Record W2156747708 · doi:10.1017/s0305741006000208

The Political Economy of Township Government Debt, Township Enterprises and Rural Financial Institutions in China

2006· article· en· W2156747708 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.

Bibliographic record

VenueThe China Quarterly · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBusinessDebtChinaFinanceLoanLocal governmentGovernment (linguistics)PoliticsResource mobilizationFinancial systemEconomic policyPublic administrationPolitical science

Abstract

fetched live from OpenAlex

This article sheds light on the ways in which township governments mobilized resources from local financial institutions, and how failure to repay many of these loans gave rise to sizeable local government debt. Mobilization of resources was done through loans to collective enterprises whose de facto owners were township authorities. Though the enterprises were nominal borrowers, loan transactions would not have occurred without guarantees by township governments. Another way of financial resource mobilization was by establishing local informal financial organizations that were subject to less strict regulations, and over which township authorities could exercise control. Further, because the enterprises' profits and taxes ultimately went to township authorities, and the enterprises also contributed towards provision of public goods that were the authorities' obligation, enterprise financing became a roundabout way in which township authorities sought financial assistance for their fiscal needs.

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)0.001
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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