Communicating Science on, to, and with Racial Minorities during Pandemics
Notice bibliographique
Résumé
Introduction Pandemics, such as Severe Acute Respiratory Syndrome (SARS) and COVID-19, can disproportionately impact migrants and racial minorities through increased morbidity and mortality (Pan et al, 2020) and limited consideration of their needs in measures to control disease spread (Tan, 2021). Furthermore, communication initiatives to educate the public about SARS and COVID-19, particularly their origin, spread, and control, can lead to stigmatisation, othering, and exclusion of Asian minorities (Hung, 2004). Although communicating the science associated with these infectious diseases can facilitate transparency and rationalise lockdown measures, they can also harm minority ethnic groups and the broader social fabric when conducted in a culturally insensitive and exclusionary manner. To illustrate the importance of sensitive and inclusive pandemic science communication, this chapter draws from accounts of two coronavirus pandemics. Before the 2020 COVID-19 pandemic, the world was threatened by SARS in 2003, especially the Canadian city of Toronto. Communication on its origin in China led to racially motivated attacks and discrimination against people who look East or South East Asian and against businesses in Toronto's Chinatowns (Keil and Ali, 2006). These forms of discrimination were also experienced by Australia's Asian minority population during the COVID-19 pandemic (Asian Australian Alliance and Chiu, 2020). However, the management of COVID-19 in Australia also highlighted the disproportionate impact of lockdown policies on racial minority and socio-economically disadvantaged groups, especially with inadequate communication of their implementation (Victorian Ombudsman, 2020) and scientific/epidemiological rationale (Patrick, 2021). These were further aggravated by limited engagement with community members in planning lockdowns (Victorian Ombudsman, 2020). This chapter draws from academic publications, reports, and news articles on SARS and COVID-19 to illustrate how different forms of communication on and during these pandemics profoundly affected the welfare of racial/ethnic minorities. Lessons from these incidents can be used to develop more inclusive ways of communicating pandemic science and formulating associated policies (Hyland-Wood et al, 2021). Experiences during SARS and COVID-19 can help develop pathways not just for communicating science involving racial minorities but also for relaying scientific information that has a profound impact on them. Going beyond communication on and to, lessons during these pandemics are vital in underscoring the importance of engaging with minorities to develop culturally sensitive communication strategies (Airhihenbuwa et al, 2020).
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».