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Record W4416975684 · doi:10.23865/magma.v28.1555

Styring og rapportering i en omskiftelig tid

2025· article· sv· W4416975684 on OpenAlexaff
Kjell Magne Baksaas, Tonny Stenheim

Bibliographic record

VenueMagma · 2025
Typearticle
Languagesv
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsAudit

Abstract

fetched live from OpenAlex

Fagområdet regnskap og revisjon preges av raske endringer og økt kompleksitet. Profesjonen kombinerer etterlevelse av lover og regler med økonomifaglig kompetanse og tekniske løsninger, men må samtidig håndtere nye risikoer og kontinuerlige tilpasninger. Dette stiller store krav til både kunnskap og fleksibilitet i arbeidshverdagen. Bærekraftsrapportering er et område i betydelig endring. CSRD-direktivet og ESRS-standardene, sammen med taksonomiforordningen, stiller omfattende krav til foretakenes rapportering. EU er nå i prosess med å redusere omfang og detaljeringsgrad gjennom Omnibus. Norske foretak kan legge EU-lettelser til grunn, og mange rapporterer også frivillig for å møte interessenter og egne mål. Samtidig begynner kunstig intelligens å påvirke måten revisorer og regnskapsførere arbeider på, særlig gjennom automatisering av rutineoppgaver. Store endringer er foreløpig på utviklingsstadiet, og kritisk skjønn, etikk og menneskelig refleksjon forblir enda viktige ferdigheter. Parallelt intensiveres digitaliseringen av bokføring og fakturering, med krav til SAF-T, EHF og elektronisk bokføring, noe som særlig berører små og mellomstore foretak. Revisjonsbransjen gjennomgår omfattende omorganisering med PE-fond på eiersiden, fusjoner og fisjoner, samt tydeligere segmentering av markeder og kunder. Regjerningen foreslår gjennom statsbudsjettet for 2026 å bidra med driftstilskudd til Norsk Regnskapsstiftelse. Dette vil gi stiftelsen mulighet til å oppdatere eksisterende standarder og utvikle nye, noe som vil bidra til å sikre regnskapsinformasjon av høy faglig kvalitet. English abstract Management and Reporting in a Changing Time The field of accounting and auditing is characterized by rapid change and increasing complexity. The profession combines compliance with laws and regulations with financial expertise and technical solutions, while simultaneously managing new risks and continuous adaptations. This places high demands on both knowledge and flexibility in everyday work. Sustainability reporting is an area undergoing significant transformation. The CSRD directive and the ESRS standards, together with the Taxonomy Regulation, impose extensive requirements on corporate reporting. The EU is now in the process of reducing the scope and level of detail through the Omnibus proposal. Norwegian companies may adopt these EU simplifications, and many also report voluntarily to meet stakeholder expectations and their own objectives. At the same time, artificial intelligence is beginning to influence how auditors and accountants work, particularly through the automation of routine tasks. Major changes are still in their development phase, and critical judgment, ethics, and human reflection remain essential skills. In parallel, the digitalization of bookkeeping and invoicing is intensifying, with requirements for SAF-T, EHF, and electronic bookkeeping—developments that particularly affect small and medium-sized enterprises.The audit industry is undergoing extensive restructuring, with private equity funds entering ownership, mergers and demergers, and clearer segmentation of markets and clients. Through the 2026 National Budget, the government proposes to provide operational funding to the Norwegian Accounting Standards Board. This will enable the board to update existing standards and develop new ones, helping to ensure high-quality financial reporting.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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