Openness to context‐based research: the gulf between the claims and actions of Big Six firms in the USA
Bibliographic record
Abstract
This paper has been written following the refusal of US Big Six firms to participate in a context‐based research project on the new‐client‐acceptance decision, in spite of their claims that current audit research is too far removed from the realities of practice. The paper aims to problematise the firms’ refusal, arguing that it exemplifies efforts at policing the development of academic knowledge on the part of gatekeepers who strive to make researchers work on technicalities, thereby mitigating the risk that research may tarnish the profession’s legitimacy. Insights into the social construction of the gatekeepers’ efforts at policing knowledge are provided by the multilateral negotiations with the firms, showing initial differences in gatekeepers’ boundaries of acceptable research, and subsequent between‐firm discussions that resulted in the firms’ joint decision to refuse participation.
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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 | 0.096 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".