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Record W2985351800 · doi:10.5539/jas.v11n18p272

Game Theory Analysis: The Stakeholder Behavior in the Rural Collective Property Rights System Reform (RCPRSR)

2019· article· en· W2985351800 on OpenAlexvenueno aff
Ammar Saad, Ying Xia

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsnot available
FundersAgricultural Science and Technology Innovation Program
KeywordsProperty rightsEnthusiasmStakeholderGame theoryChinaImplementation theoryGovernment (linguistics)Economic systemNash equilibriumStakeholder theoryBusinessEconomicsPublic economicsEconomic growthMicroeconomicsPolitical scienceRepeated gameManagement

Abstract

fetched live from OpenAlex

The Rural Collective Property Rights System Reform (RCPRSR) is a process of evolution along with the equilibrium point of the game theory. It is also an institutional change involving China’s primary economic system and rural basic management system. This paper used the stakeholder theory to determine the main stakeholders in the RCPRSR and then analyzed the behavior mechanism of the main stakeholders through the method of game theory. The results indicate that the main stakeholders are farmers, village organizations, and government. The Nash equilibrium solution is executing and joining respectively village organizations and farmers. Game theory also suggests that the RCPRSR is a gradual and repetitive dynamic process, not the result of one-time rational design. Based on the conclusions of the research, it indicates that should raise the enthusiasm of the village organization. This can increase the income of farmers and flourish the rural economy of China.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.210
Teacher spread0.190 · 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 designSimulation or modeling
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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