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Record W4414895494 · doi:10.26481/dis.20251029gs

The law and economics of employee participation in corporations

2025· dissertation· en· W4414895494 on OpenAlexaff
Guotong Shen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsLaw Foundation of Nova Scotia
Fundersnot available
KeywordsChinaCorporationEmployee engagementEmployee researchEmpirical researchIndustrial relationsEmpirical evidenceLabour law

Abstract

fetched live from OpenAlex

Parties in a corporation do not always share the same interests. Such conflicts can be reduced by employees participating in corporate management or by sharing in financial benefits. In light of the significant revisions to provisions related to employees and employee participation in China’s 2023 Company Law, this thesis examines how employee participation has been developed and structured in China and its effects on employees and on firm performance. To answer this research question, this thesis employs a law and economics approach to provide economic justifications for employee participation. Building on existing empirical literature, this thesis demonstrates, through quantitative analysis, the positive effects of financial participation on the performance of Chinese state-owned enterprises. It also compares relevant regulations in China with those in Germany. Furthermore, it finds that employee participation in China has a unique social, political, and economic context, particularly influenced by Confucianism and socialism.

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)0.004
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: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.011
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.246
Teacher spread0.227 · 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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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