Attracting Prospective Professional Accountants Before and After the <scp>CPA</scp> Merger in Canada
Bibliographic record
Abstract
Abstract As part of the unification of the Canadian accounting profession, a lot of effort has been devoted to organizational structures and systems. In these times of change, recruitment of prospective professional accountants remains an important factor for the Canadian and international development of the profession. In this paper, we explore professional accountants’ recruitment by accounting associations in Ontario before ( CA , CGA , CMA ) and after ( CPA ) the merger of the three professional accounting associations. We use a legitimacy framework to make sense of the recruitment website content of each association. We find, in the post‐merger period, that the CPA profession adopts a more passive approach to legitimacy management, focusing mainly on exchange aspects of legitimacy, whereas prior to the merger a wider range of legitimacy management strategies were deployed by the predecessor associations. Important implications ensuing from our study are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".