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Record W2970845283 · doi:10.5539/jpl.v12n5p15

The Reform of the Civil Service System in China 1993–2009

2019· article· en· W2970845283 on OpenAlexvenueno aff
Guzel Vasilevna Rakhimova, Dmitry Evgenyevich Martynov, Yulia A. Martynova, Glushkova Svetlana Yurievna

Bibliographic record

VenueJournal of Politics and Law · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Administration and Governance
Canadian institutionsnot available
FundersKazan Federal University
KeywordsCivil servantsDismissalIncentivePublic administrationCivil serviceInterimChinaPolitical scienceLegalizationControl (management)Power (physics)Public servicePublic relationsLawManagementEconomicsPoliticsMarket economy

Abstract

fetched live from OpenAlex

The paper is devoted to the analysis of public service reforms in China in the period of 1993 - 2009. The reforms, in part, took advantage of the positive experience of the Chinese past. They were aimed at improving the efficiency of civil servants by introducing more competitive selection processes, incentives to encourage activities and tightening control and supervision. The processes of selection, appointment, training, dismissal and retirement of civil servants were also streamlined. The chronological scope of the study is determined by the dates when the Interim Regulation on Civil Servants (1993) was adopted, and up to the date of adoption and implementation of the full-fledged Law on Civil Servants (2006). Then the first consequences of the reforms began to be felt: the legalization and normalization of the personnel system, the motivation to show high moral standards for civil servants who could gain respect from the people, and the activation of their high moral and business qualities. In part, the adoption of these laws was accompanied by the coming to power of the fourth generation of leadership of the CPC and PRC.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.852

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.009
GPT teacher head0.269
Teacher spread0.260 · 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 designNot applicable
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

Citations1
Published2019
Admission routes1
Has abstractyes

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