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The Practice of Policy about Corporate Environmental Information Disclosure in China——Data From A-Share Listed Companies of Heavy Polluting Industries

2014· article· en· W1735702061 on OpenAlexvenueno aff
Tang Jian, Peng Jue, Yang Zhou

Bibliographic record

VenueCanadian social science · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAccountingCorporate governanceSample (material)Order (exchange)Environmental accountingQuality (philosophy)Finance

Abstract

fetched live from OpenAlex

Corporate environmental disclosure policy is a system tool to solve the environmental information asymmetry problem, it has an extremely important significance to improve public participation in environmental activities, and promote the improvement of corporate environmental performance. However, there is less literature about the direct corporate environmental information disclosure policy, and these studies are mostly qualitative or small sample studies, reliability is low. In this paper, all the listed companies of A shares heavily polluting industries are studied as a large sample to research the health of corporate environmental information disclosure system, in order to find out that the system operation runs low performance, the quality of environmental information disclosure is not good enough, revealing the main reason lies in the system is unreasonable design, the poor independence of the regulatory authorities, and then, put forward some specific proposals. Objective: To investigate the practice of corporate environmental information disclosure policy, reveal its cause. Results: around seventy percent of heavily polluting industries listed companies have disclosed environmental information; the disclosure of the information mostly described in text or data; majority of environmental information disclosed in the Report of the Board of Directors or Accounting Statements; the disclosure of the mainly contents of environmental management and environmental governance; large gap between inter-industry enterprises  in the quality and quantity of environmental information disclosure. Research limitations and significance of research: This article examines only the data of corporate environmental disclosure policy operation of 2010, is a cross-sectional study. Follow-up longitudinal studies should be carried out to study the changes in corporate environmental disclosure before and after the implementation of the policy, empirical test whether the policy has a substantial impact on corporate environmental disclosure. Practical significance: this article summarizes the problems of corporate environmental disclosure, reveals its cause, and puts forward a reasonable proposal, which has an important reference value for government decision-making. Innovation and value: select all the listed companies of heavily polluting industries of 2010 as study sample firstly, to reflect the most important aspects of corporate environmental information disclosure policy runs.

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)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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