Big 4 offshore: Transparency arbitrage across legal and geographical boundaries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract How do global firms manage conflicting constituencies in complex markets? The Big 4 accounting firms have expanded their size and scope to the extent that they need to relate to different constituencies simultaneously, sometimes on controversial issues. This is particularly relevant given their engagement in aggressive tax planning services alongside their traditional professional obligations, as this generates a conflict between discretion offered to “offshore” clients and accountability offered to other stakeholders. This requires strategic duplicity—sending differentiated signals to different stakeholders. We suggest that firms use organizational partitioning across legal structures and geographies to enable strategic duplicity. We test this by collecting a unique data set on the Big 4's ownership structures and staff numbers across all locations, showing that their organizations are heavily segmented. We show that the Big 4 use this geographical and legal differentiation to send contrasting signals to constituents about their organizations, engaging in a type of strategic duplicity that we term transparency arbitrage, in which “onshore” stakeholders receive a signal of transparency and “offshore” stakeholders receive a signal of discretion. This duality enables them to engage in controversial issues with conflicting stakeholders.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it