Teaching Management Control Dysfunction Using Observations of <scp>CEO</scp> Leadership at Wells Fargo <sup>*</sup>
Bibliographic record
Abstract
ABSTRACT The focus of this teaching case is an actual instance of management control (MC) dysfunction that was prompted by ongoing crises at Wells Fargo Bank. MC is an interdisciplinary field of learning that integrates a variety of management disciplines, such as leadership, accounting, performance measurement, governance, and ethics. The case uses the official transcript of questioning of the then‐CEO of Wells Fargo, John Stumpf, by Senator Elizabeth Warren during a US Senate hearing entitled “An Examination of Wells Fargo's Unauthorized Accounts and the Regulatory Response.” Exposure of the “unauthorized accounts” was a forerunner to the highlighting of several Wells Fargo scandals in following years. At times, the questioning of Stumpf was adversarial, and it provides an opportunity to examine leadership‐in‐action from an MC (and related) perspective. By employing real company events, we demonstrate how to develop an understanding by students that MC is a multifaceted, interdisciplinary area of learning. The case enhances students' opportunities to critically evaluate MC‐in‐action.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".