Learning the “Craft” of Auditing: A Dynamic View of Auditors' On‐the‐Job Learning
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 We investigate how auditors learn the technical aspects of their professional role while performing client engagements, and how that learning process has been shaped by changes in societal, economic, and regulatory forces. Prior studies explicitly recognize that auditors need social skills and demeanor consistent with professional norms as well as requisite knowledge, but those studies generally focus on the processes through which new auditors are molded toward consistency with social norms. In contrast, we focus on forces affecting the transfer of technical knowledge from supervisor (guide) to subordinate (learner) in the everyday work setting. Our evidence derives from semi‐structured interviews with 30 relatively new and more experienced audit partners at one Big 4 firm, thus spanning multiple “generations” of experience. Results confirm that auditors primarily acquire technical knowledge on the job, through the interactions among individual engagement team members. However, partners express concern about changes in the practice environment that may limit effectiveness of on‐the‐job learning, including characteristics of personnel, the approach to formal training at induction, supervisors' reluctance to provide candid feedback, regulatory and economic pressures, and the increased distraction, and reduced interpersonal contact associated with the use of information technology. At the end of the day, our findings raise implications for practice regarding the difficulty of developing effective learning conditions for auditors in the face of these challenges.
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.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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