Bibliographic record
Abstract
Purpose The American Institute of Certified Public Accountants (AICPA) recently proposed a global consulting credential involving a diverse set of professions including accountancy, business law, and information technology. The proposal was widely debated in the professional literature, and was a divisive issue among CPAs. In late 2001, the AICPA membership voted against any further commitment to the credential. The purpose of this paper is to examine the global credential initiative in an effort to understand why professional jurisdictional claims may fail at the theorization stage. Design/methodology/approach The paper relies primarily on a qualitative review and analysis of archival materials and published articles and commentaries relating to the global credential project. Findings The analysis indicates that the AICPA failed to establish either the pragmatic or moral legitimacy of the proposed credential in the eyes of the audiences. This failure appears to be attributable to the sociopolitical environment in which the credential was promoted, and to flaws in the rhetoric used by the AICPA to articulate its jurisdictional claim. Research limitations/implications The paper demonstrates the importance of legitimacy to the ability to successfully theorize institutional changes. Originality/value This paper investigates how the AICPA theorized the global credential knowledge claim, and how theorization failed to persuade the audiences to support the credential.
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 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 | 0.100 | 0.247 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".