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Record W3018498067 · doi:10.14783/maruoneri.703333

ÇEVRE MUHASEBESİ (Environmental Accounting-Green Accounting)

2020· article· tr· W3018498067 on OpenAlexaboutno aff
Ümit GÖKDENİZ

Bibliographic record

VenueÖneri Dergisi · 2020
Typearticle
Languagetr
FieldSocial Sciences
TopicPublic Administration and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental accountingAccountingBusinessEnvironmental science

Abstract

fetched live from OpenAlex

The aim of this stuıly is to present “accounting for the environment” or “Green Accounting” which has a new concept in the area of the classic accounting thinking and the practices. Many studies and regulations lıave been done by the European Union, The United States, Canada, The Republic of South Africa, International Organizations, Academic Institutions, IFAC (International Federations of Accountants) and others. Accounting for the environment which is a relatively recent development in accounting thinking, has evolved from the notion that business entities have, in addition to their primaıy object of profıt maximization, a social responsibility as v/ell: Nowadays companies are experieııcing and respond- ing to challenges presented by the environmental crisis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0510.027

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 head0.022
GPT teacher head0.265
Teacher spread0.243 · 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
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

Citations3
Published2020
Admission routes1
Has abstractyes

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