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Record W3198034088 · doi:10.3390/jrfm14090417

Non-Financial Reporting—Standardization Options for SME Sector

2021· article· en· W3198034088 on OpenAlexvenueno aff
Patrycja Krawczyk

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsStandardizationBusinessAccountingSustainabilitySustainability reportingFinanceResource (disambiguation)Accounting managementPerspective (graphical)Accounting information systemComputer science

Abstract

fetched live from OpenAlex

Non-financial reporting is the basic tool for presenting the implementation of sustainability goals (SDGs). This paper investigated the current status of non-financial reporting standardization in terms of small and medium-sized enterprises. The topic of non-financial reporting has been discussed in recent years from the perspective of large business entities. So far, it has only rarely been applied to SMEs. This will increase significantly in the coming years when such reports will also become obligatory for smaller entities. The first stage of the research, based on the method of analysis and criticism of the literature, will be prepared in the area of the subject taken, including relations between the main concepts: sustainability, non-financing reports, SMEs. The essential data source used for the article is reports published by the Global Reporting Initiative. Based on the research conducted, it can be concluded that it is necessary to develop non-financial reporting standards for SMEs. These results may become a valuable resource of knowledge and a set of samples that can be useful in developing this area. Especially since it can be expected that such reports will also be obligatory for SMEs.

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 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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.256
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations35
Published2021
Admission routes1
Has abstractyes

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