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Professionalism, Professional Commitment, and Performance

2023· book-chapter· en· W4322506807 on OpenAlexaff
Stuart Thomas

Bibliographic record

VenueAdvances in accounting behavioral research · 2023
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsContinuanceObligationNormativePsychologySocial psychologyPublic relationsProfessional associationProfessional studiesOrganizational commitmentProfessional ethicsProfessional developmentPolitical sciencePedagogyLaw

Abstract

fetched live from OpenAlex

Abstract The current study examines public accountants' professionalism and professional commitment (PC) and their effect on job performance. Results provide support for four of five dimensions of Hall's (1968) professionalism framework (beliefs in professional affiliation, professional dedication, self-regulation, and social obligation) and Meyer et al.'s (1993) three-dimensional PC framework (affective, continuance, and normative professional commitment) for modeling public accountants. Support was also found for most of the hypothesized relationships between professionalism and PC. Beliefs in professional affiliation, professional dedication, and self-regulation positively influenced affective professional commitment (APC). Belief in professional affiliation was negatively influenced by continuance professional commitment (CPC) but positively influenced by normative professional commitment (NPC). Belief in social obligation was also positively influenced by NPC. As expected, professionalism and PC were associated with job performance. Professionalism had an incremental effect beyond PC on job performance and as well, PC had an incremental effect over professionalism on job performance. Identifying relationships between professionalism and professional commitment with desirable outcomes is important for justifying future investments in the public accounting profession. Understanding these issues will assist in determining the types of professional attributes and commitments that are and should be fostered by the accounting profession.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.731
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 studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.146
GPT teacher head0.426
Teacher spread0.280 · 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 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

Citations5
Published2023
Admission routes1
Has abstractyes

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