Risk Planning and Management in Portuguese Companies—A Statistical Approach
Bibliographic record
Abstract
The purpose of this article is to study risk management planning and risk management in Portuguese companies. The methodology used is of a quantitative nature, based on a questionnaire survey that analyzes the risk management planning and risk management of 1647 Portuguese companies from different sectors of activity. The results allow us to conclude that the aspects that most manifest themselves in the perceptions of risk management planning are having a management plan that includes the relationship with customers, suppliers, and employees, as well as an updated security plan. This study intends to contribute to academic knowledge and for companies to know and master the concepts of risk management planning and risk management in its different aspects, helping the adoption of strategies to better plan risk management. The results make it possible to understand the differences in planning and risk management between larger and smaller companies, between older and younger companies, and between family and non-family companies. These results can contribute to increasing corporate sustainability and improving performance in planning and managing corporate risks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".