The Colonization of Public Accounting Firms by Marketing Expertise: Processes and Consequences
Bibliographic record
Abstract
SUMMARY This paper highlights the colonization of public accounting firms by marketing expertise. Using data collected through interviews with auditors and marketing experts, complemented with data generated through documentary analysis, we examine the marketing-oriented transformations that took place in public accounting firms and the important outcomes ensuing from the spread of marketing ideology to the field of auditing. To carry out this work, we developed a customized conceptual framework aimed at enriching our understanding of the “marketization” of public accounting. Empirically, we document the development of various marketing strategies and the underlying translations of public accounting firm day-to-day activities (in terms of business relationships and technical advice) into marketing language. Our findings point to the transformation of public accountants to “part-time” marketers. The results are also suggestive of the colonization of public accountants' minds, whose core values are being subjected to the influence of marketing expertise. This shift engenders important consequences, particularly in potentially compromising auditor independence.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".