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Record W3011722979 · doi:10.5430/rwe.v11n1p143

Corporate Environmental Disclosure Practices in Vietnam

2020· article· en· W3011722979 on OpenAlex
Nguyễn Vĩnh Khương, Thai Hong Thuy Khanh, Phung Anh Thu, Bui Ngoc Linh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch in World Economy · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
FundersTrường Đại học Kinh tế - Luật, Đại học Quốc gia Thành phố Hồ Chí Minh
KeywordsBusinessSustainabilityCorporate governanceAccountingSustainability reportingCorporate sustainabilityFinance

Abstract

fetched live from OpenAlex

The purpose of the paper is to examine the extent of corporate environmental disclosure (CED) made by some major Vietnam listed firms (VLFs) on their annual reports, corporate governance reports and sustainability reports (if any) for the years 2017 to 2018 since some firms have not published sustainability reports for the year 2018 yet. And study also aims to support people with the overview of the importance and level impact of CED for business operations and stakeholders as well. Hence, with the theoretical framework of CED, international experience of CED, and the examination of situation of CED of some major VLFs in Vietnam, we would like to create the motivation, aspiration for readers to learn more about CED so that the form of disclosing environmental information will become familiar with other company annual reports.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.209
GPT teacher head0.354
Teacher spread0.145 · 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