Bibliographic record
Abstract
When a corporation fails to effectively deal with a crisis, the consequence is often the exacerbation of the crisis into other areas of the organization which ultimately causes the original crisis to evolve into a disaster.Disasters frequently result in the death of the organization.The tenets of corporate crisis management are no longer sufficient in today's dynamic envi ronment.Organizations must take a proactive and comprehensive approach to crisis management in order to maintain an acceptable level of risk.This research paper examines the relevant research on crisis models, the factors that contribute to crises, risk reduction, responses, people management, communications, stakeholder relations, eth ics, correctional action and recovery.The review of the literature identified the growing trend for organizations to utilize crisis teams to direct the crisis management process.With increasing threats posed to organizations, a single individual is no longer sufficient to co-ordinate the crisis management process; teams are better equipped to deal with the complex and ambiguous nature of crises .The crisis management team's responsibilities include risk identification and reduction, preparation, early signal detection, crisis management, organizational recovery, prevention and learning.Crisis management teams will play a growing role in the continuing viability of corporations.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".