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China and Development Economics

2008· book-chapter· en· W290301114 on OpenAlex
Alan Heston, Terry Sicular

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

VenueCambridge University Press eBooks · 2008
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhenomenonIndustrialisationChinaProductivityCorporate governanceEconomicsPosition (finance)Agricultural productivityDevelopment economicsPolitical scienceEconomic growthRegional scienceGeographyAgricultureManagementMarket economy

Abstract

fetched live from OpenAlex

We view development economics as a set of empirical generalizations, paradigms, and tools that tell us something about why large differences in productivity and income within and among countries, social groups, and classes seem to persist. How does China fit into the received views of development economics? In answering this question the cup overfloweth with materials, so no attempt is made to be exhaustive. We begin in Part A by using comparative statistics of developing and developed countries to help understand China's present position and its growth experience since 1978. Ensuing sections take up selected topics where development economics and China's development experience intersect. Part B looks at governance issues in a comparative framework, focusing on corruption as a phenomenon that brings together many features of administration that are common across countries. Part C examines the rural sector, focusing on agricultural productivity and land tenure, and Part D reviews the uniquely East Asian phenomenon of rural industrialization. Part E concludes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.984
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.202
Teacher spread0.176 · 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