The Social Construction of Risk: Evidence from UK Banks
Bibliographic record
Abstract
This research presents empirical evidence of the perceptions of risk in UK operating banks and how these perceptions influence risk processes at these institutions. We used social constructivism to understand the views of UK managers in the banking industry. The study found that there was a divide in risk perception among risk managers in UK operating banks. Such a divide is crucial in explaining the differences in risk approach and risk processes in the banking industry. The discussion presented is based on the results of 25 semi-structured interviews. Two distinct characterizations of risk emerged from the data. One perceived risk as a calculable, measurable construct that can be managed, controlled and verified. The other conceived risk as a mixture of mathematical numerics and social ideals that engages an understanding of and appreciation for the concept. Each viewpoint represents an opportunity to fathom risk in its own context, contributing to the critical debate on risk management. The extent to which social factors influence risk decisions varied among banking institutions. Keywords: risk, risk management, social construction, banks
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".