Crisis Command: Strategies for Managing Corporate Crises
Bibliographic record
Abstract
A quarter of crisis-hit organisations do not survive,' Journal of Contingencies and Crisis Management, 2004. Is your organisation equipped with the necessary tools to respond quickly and effectively to any type of crises? A lack of a clear defined strategy can have far-reaching repercussions on revenue, incoming work and reputation. Ark Group's new Crisis Command report is a practical, how-to guide, packed with key strategies and realistic advice to help you prepare for and manage organisational crises. It provides valuable guidance on how to take command, how to communicate, how to work as a team facing unprecedented pressure and scrutiny, particularly from stakeholders, and how to emerge stronger. Key case studies and contributions from researchers and expert practitioners around the world will also provide you with proven solutions and mechanisms used to respond to crises, overcome disaster and protect your firm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".