Learning from the pandemic: Building capacity for risk communication in the Canadian federal health portfolio
Notice bibliographique
Résumé
SETTING: The federal health portfolio has had a risk communications framework in place since 2006; however, the COVID-19 pandemic pushed the capacity of this plan and the need for communications resources to new levels. Health communicators in the public service face significant challenges: a fragmented mediascape, changes to how people seek and use information, the proliferation of misinformation and disinformation, declining trust in public institutions, and the politicization of science, to name just a few. It has never been more important for health authorities to communicate clearly, consistently, effectively, and from an evidence-based position. INTERVENTION: This report describes one aspect of how the federal health portfolio has been addressing these challenges. As part of a recent capacity-building initiative, 67 public servants working in health communications participated in a four-part, half-day, advanced seminar series at Carleton University in June 2023. Each session featured an interactive presentation from a leading scholar and/or local practitioner with real-world scenario exercises designed to put their learning into practice. The series explored issues in trust and transparency, algorithmic control and mis- and disinformation, media relations, and risk communication for equity-deserving populations. OUTCOMES: At the conclusion of the program, participants were given tools to (1) identify challenges to effective communication brought by a rapidly evolving media environment in which skepticism and misinformation often run rampant; (2) examine how key metrics and behavioural indicators on social media platforms demand different responses from health organizations and agencies who are monitoring and managing social media; (3) consider challenges for health communicators who must serve the public during health crises while also reinforcing public trust in their institutions; and (4) develop successful risk communication strategies for equity-deserving communities by considering specific information needs and tailored dissemination methods to reach the intended audience. Participants expressed high levels of satisfaction in the quality of the training and overwhelmingly reported that it would positively impact their daily work. IMPLICATIONS: The training program was an innovative and successful initiative to improve knowledge of current priority topics and best practices in risk communication. It illustrated the benefits of continued professional learning, the importance of university-public service partnerships, and how capacity building requires ongoing resource commitments and engaged support from senior management. The program, along with other risk communication training that is currently being implemented, is part of the investment in long-term professional development of risk communicators in the health portfolio.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,042 | 0,011 |
| Communication savante | 0,013 | 0,007 |
| Science ouverte | 0,006 | 0,021 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».