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Record W2141093277 · doi:10.5539/ibr.v7n2p22

Multidimensional Perspective and Making Up the Shortcoming of the Performance Appraisal of Public Sector in China

2014· article· en· W2141093277 on OpenAlexvenueno aff
Yong Du, Jiali Han

Bibliographic record

VenueInternational Business Research · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsnot available
FundersSouthwest University
KeywordsPublic sectorDiathesisPerformance appraisalPoliticsDutyUnificationChinaBusinessEconomicsPublic economicsIndustrial organizationMarketingComputer sciencePolitical scienceManagementLaw

Abstract

fetched live from OpenAlex

The performance management of public sector is when the public sector perform its public duty actively, on the basis of the unification of intestine management and exterior benefits, quantity and quality, economic factor and ethic political factor, rigidity criterion and soft criterion, the process to obtain the largest pubic output. The organization review and evaluate the performance of public personnel, such as politics diathesis, representation of operation, behavior of action and harvest of work, then implement rewards and punishment, in order to offer the power of inspiriting the public personnel to improve their behavior, and achieve the goal of increasing the integer efficiency of the public sector finally. Text point out the miss and drawback of performance appraisal of public sector in China, and try to put forward some solutions.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0030.003
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.331
Teacher spread0.284 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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