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Record W2612949421 · doi:10.1111/1911-3838.12139

Merging the Profession: A Social Network Analysis of the Consolidation of the Accounting Profession in Canada

2017· article· en· W2612949421 on OpenAlexaffvenueabout
Alan J. Richardson

Bibliographic record

VenueAccounting Perspectives · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPoliticsDominance (genetics)AccountingLegislationConsolidation (business)CertificationLegislatureProfessional associationPower (physics)Political scienceBusinessPublic administrationPublic relationsLaw

Abstract

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Abstract The merger of Chartered Accountants (CAs), Certified General Accountants (CGAs) and Certified Management Accountants (CMAs) in Canada to create the Chartered Professional Accountant (CPA) designation is analyzed, using social network theory. The analysis examines the conversion of market power into political power through the legislative apportionment of council seats among the three legacy bodies. It then documents how political power affects the hiring of former senior association staff from each of the three predecessor bodies to run the merged association. Social network theory suggests that these appointments could be used to fill “structural holes” to ensure effective integration of the profession postmerger or could be used by those gaining political power within the network to reinforce their control over the merged association. The analysis shows that (i) the legislation consolidating the profession converted the market dominance of the formerCAs into political dominance, (ii) formerCAinstitute executives were disproportionately appointed to runCPAassociations, and (iii) in some provinces, no connection to the knowledge base of other legacy bodies through staff appointments at an executive level was maintained. The results raise concern about the loss of social capital through the hiring process and the effects of the continued use of political power to structure the merged association on the profession's stability and resilience given the diversity of its members.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.033
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.011
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2017
Admission routes3
Has abstractyes

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