Connecting Crisis Communication Theory and Canadian Communication Research
Bibliographic record
Abstract
In the first article in this special issue, Crisis, Communication, and Canadian Hospitals: An Analysis and Evaluation of Risk Preparedness and Crisis Communication Efforts of Ontario Hospitals, Sebastian Dobosz presents the findings of interviews with 14 communication practitioners from Ontario hospitals about the state of crisis communication and management Timothy Coombs' (2004) Situational Crisis Communication Theory posits that victims of crises face no blame from the public because they have no control over their causes (public blame is a key consideration in crisis communication research as it hurts one's public reputation, which is valuable currency in the public sphere) On politics and crisis communication, the third article in this special issue, Anatomy of a National Crisis: The Canadian Federal Government's Response to the 2015 Kurdi Refugee Case by Sara Siddiqi and Duncan Koerber, similarly considers a crisis that grabbed the world's attention and negatively affected the public reputations of two Canadian politicians who actually had no hand in causing it The article examines in detail the crisis response after the 2014 terrorist attack on Parliament Hill in Ottawa that killed Corporal Nathan Cirillo Since no single governing body existed in Canada to deal with terrorist attacks, several organizations came together
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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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.024 |
| Science and technology studies | 0.048 | 0.045 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 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 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".