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Record W3015038303 · doi:10.1080/09639284.2020.1737157

Patterns underlying required competencies for CPA professionals: a content and cluster analysis of job ads

2020· article· en· W3015038303 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAccounting Education · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsAccountingAccreditationContext (archaeology)Content analysisManagement accountingAdaptation (eye)BusinessPsychologyPublic relationsMarketingPolitical scienceSociology

Abstract

fetched live from OpenAlex

In today's dynamic environment, the adaptation of the accounting profession to meet actual socio-economic needs is a challenging, and yet necessary, task. This study analyzes the technical competency requirements signalled in 171 online job advertisements for accounting positions by Canadian organizations and contrasts them with the CPA Canada competency framework, which serves as the basis for the training and accreditation of professional accountants. Following a content and a cluster analysis of the job ads, three well-separated and meaningful profiles of positions are uncovered based on technical competencies that Canadian organizations required when hiring accountants: the financial reporting, the tax aggressiveness, and the performance management profiles. From a practical standpoint, this study provides the Canadian accounting professional body, as well as educators in the accounting field, with insights regarding the expectations of the job market. The study also has implications in accounting education beyond the Canadian context.

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.

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)0.001
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 score0.053
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.091
GPT teacher head0.315
Teacher spread0.224 · 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