Networks of interpretation: An ethnography of the quest for IFRS consistency in a global accounting firm
Bibliographic record
Abstract
Because of their complexity and principle-based nature, the creation of International Financial Reporting Standards (IFRS) engendered significant uncertainty that modified the order of things within large accounting firms. This motivated them to establish Professional Practice Function (PPF) units to try to ensure a credible degree of consistency in applying IFRS across a wide range of financial reports at the international level. We study backstage dynamics surrounding a PPF national unit in one of the Big Four firms. We focus on the rise of the PPF as an expert-based control device within the firm, and the role PPF members play as knowledge brokers to interpret IFRS. Our investigation is carried out through ethnographic fieldwork supplemented by interviews with PPF members and field auditors. The analysis brings forward some of the organizational dynamics surrounding PPF members' efforts to establish their credibility as intermediaries both hierarchically, between administrative partners and field auditors, and epistemically, between the unifying logic of IFRS and auditees' financial reporting specifics. Ultimately, our analysis points to the role of the PPF as a gatekeeping or internal control device that mediates between different pools of knowledge to monitor the firm's reputation risk against IFRS implementation challenges. From a legal perspective, our ethnography documents how accounting “law” is made at the firm level and how PPF members strive for consistency – in spite of significant epistemological and organizational challenges. Our ethnography also shows that complex IFRS interpretation issues are not resolved through one person's judgment; instead, the firm's structure surrounding the PPF allows for the constitution of inter-individual judgment that transcends national, sectoral, and (sometimes) organizational boundaries. Finally, we see one important contribution of our work as helping reveal the limits of large conceptual categories such as “auditors”, which tend to downplay the dynamics of convoluted practice relationships.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".