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Record W2787569662 · doi:10.5430/ijba.v9n2p1

Prospects of Application of International Standards in Financial Reporting by Small and Medium-size Businesses in Georgia

2018· article· en· W2787569662 on OpenAlexvenueno aff
Levan Sabauri, Nadezhda Kvatashidze

Bibliographic record

VenueInternational Journal of Business Administration · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsInternational Financial Reporting StandardsBusinessAccountingSmall and medium-sized enterprisesFinanceTask (project management)Financial ratioEconomics

Abstract

fetched live from OpenAlex

Drafting financial statements according to the complete (global) International Financial Reporting Standards (IFRS) in place by small and medium-size businesses (enterprises) is a laborious and costly task, so much so that it does not comply with the cost-utility ratio guideline of the IFRS conceptual framework.The International Accounting Standards Board (IASB) developed financial reporting standards adequate with the transactions, deals and information users of the small and medium-size businesses, which resulted in simpler IFRS and ultimately cheaper financial statements and more useful information. Most of the businesses in Georgia are small or medium-size, so simplified IFRS allow them not only to supply information without much effort and excessive costs but develop further and attract investments.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.055
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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 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

Citations6
Published2018
Admission routes1
Has abstractyes

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