Moral Accounting by Organizations: A Process Study of the U.S. Financial Crisis Inquiry Commission
Bibliographic record
Abstract
We take an inductive approach to understanding the aftermath of crises, namely, the process by which organizations come to be viewed as morally accountable (or not) for such events. We studied the transcripts of the 2009 Financial Crisis Inquiry Commission (FCIC) that investigated the global financial crisis of 2007-2008. Our findings revealed a dynamic we call moral accounting, a process whereby supposed wrongdoers encounter narrative and situational constraints that make it difficult, if not impossible, to fully account for the (im)morality of their actions, a position that often induces moments of disorientation that only reinforce the perception of wrongdoing. To push back against such perceptions, supposed wrongdoers use rhetorical strategies and sentence-level linguistic tactics, which can likewise reinforce the perception of wrongdoing. Overall, our model suggests that organizational moral accountability is not simply assigned, accepted, or denied—rather, it is negotiated via an iterative, discursive process.
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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 | 0.023 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".