Risk Perception, Accounting, and Resilience in Public Sector Organizations: A Case Study Analysis
Bibliographic record
Abstract
There are various factors that can affect an organization’s ability to overcome a crisis and the uncertainties that arise thereafter. Little is known about the process of organizational resilience and the factors that can help or prevent it. In this paper, we analyzed how public sector organizations build resilience/traits of risks awareness, and in doing that, we derived some elements that could affect the process of resilience. In particular, drawing on the conceptual framework proposed by Mallak we analyzed an in-depth case study in a public sector organization (PSO) identifying some contextual dimensions implicated in the process of building resilience. In our analysis, we identified two main elements that affect resilience: Risk perception and the use of accounting. Results shown how risk perception is perceived as a trigger, while accounting is considered as an enforcer in the process of building resilience capacity. The results also show the way accounting is implicated in the management of austerity programs and supporting the creation of a resilient public sector organization. In our case, the risk has become an opportunity for change. In the face of these budget cuts, management began refocusing the company’s mission from infrastructure maintenance to providing services with a market-based logic.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".