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Record W2335514648 · doi:10.1108/mf-12-2014-0319

Accounting-education trends by authors from Australia, Canada, New Zealand and the United Kingdom

2016· article· en· W2335514648 on OpenAlexaboutno aff
Richard A. Bernardi, Taylor L. Delande, Kimberly A. Zamojcin

Bibliographic record

VenueManagerial Finance · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingPublicationOriginalityAccounting researchPositive accountingNational accountsAccounting information systemFinancial accountingPolitical scienceSociologyEconomicsSocial scienceLaw

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to examine the trends in accounting-education publications and the influence of journal rankings for authors from Australia, Canada, New Zealand and the UK. Design/methodology/approach – The authors included the publications in ten accounting-education journals for the 20-year period from 1993 to 2012. Findings – The data provide insights into the perceptions of accounting-education journals by authors from four countries. The authors found that, while the use of Accounting Education as a publication outlet for accounting authors from Australia and the UK was relatively stable, the use of Accounting Education as a publication outlet increased (decreased) for the accounting authors from New Zealand (Canada). The authors also found that, while coauthoring by the accounting authors from Australia and the UK increased slightly, coauthoring by the accounting authors from Canada and New Zealand increased during the 20-year period. Research limitations/implications – The data suggests a tendency by the authors from these four countries to publish their accounting-education research in journals that had been ranked as a top accounting journal. Originality/value – This paper is the first paper to consider trends in international accounting-education publications. The data in this research can be used by accounting faculty wishing to assess which journals their colleagues publish in most frequently.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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