Investigating the Role of Professional Accounting Education in Enhancing Meta-Competency Development
Bibliographic record
Abstract
A broad set of business competencies, meta-competencies (MCs), include influencing/persuading, teamwork/relationship building, critical/analytical thinking, self/time management, leadership, strategic thinking, presentation, and communication. This chapter incorporates research from two studies examining MCs in undergraduate and professional business programs. The MISLEM project found that, in comparison to graduates, employers demonstrated less optimism about graduates' competencies. Subsequently, Morpurgo investigated differences in the perception of competency acquisition between professional accountants (PAs) and supervisors in Canada by posing three questions: 1) Is there a MC importance gap between Canadian PAs and their supervisors? 2) Do professional accounting programs contribute to bridging the MC capability gap? and 3) What factors contribute to MC development? The study found perceptual differences between PAs and supervisors regarding the importance and capability of MCs as well as differences in work experience and classroom learning for competency development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".