Charles T. Adeyanju. Deadly Fever: Racism, Disease, and a Media Panic
Notice bibliographique
Résumé
Charles T. Adeyanju. Deadly Racism, Disease, and a Media Panic. Halifax-Winnipeg: Fernwood Publishing, 2010. 132 pp. $17.95 sc. There are several things the audience should know before reading this book. First, a commitment to critical theory provides a key reminder: References to may not be real in the empirical/objective sense of the concept; nevertheless, the concept is real because people act as if it was real, with sometimes catastrophic consequences, thus confirming W. I. Thomas's prescient notion that unreal' (symbolic) phenomena can yield real (objective) effects. Second, mainstream newsmedia are racialized--not because of systematic (deliberate) racism--but because this coverage is systemically (unintended consequences) biasing, thanks to the predominantly negative framing of diversities and difference implicit in a prevailing media gaze. Third, the centrality of framing as a process for organizing information. Framing as persuasion draws attention to some aspect of reality as normal and acceptable, yet away from other dimensions of reality as irrelevant and inferior, in the process encouraging a preferred reading without reader/viewer awareness of their complicity or of the biases at play (hegemony'). Fourth, the concept of media hype and moral panic. Newsmedia are prone to exaggerate and sensationalize incidents or events because it's in their institutional nature to do so, often for self-serving reasons. This amplification of scare stories is not without consequences for spooking the general public into panic mode and politicians into hasty decisions. Once equipped with this knowledge, Deadly Fever begins to take shape as an empirically informed and theoretically valuable book. Much of the content and argument can be gleaned from perusing the backcover and preface. In early February 2001, the Hamilton Spectator published an article linking (erroneously as it turns out) a hospitalized Congolese woman with the possibility of importing into Canada a deadly infectious disease known as Ebola. As the author and others note, there is a long history of associating disease with and nationality (SARS or bird flu as Chinese diseases, HIV/AIDS with Haiti), in effect demonstrating the subtle and not-so-subtle ways in which the intersection of race, nationality, and gender are played out in those contemporary societies espousing a code of without race Although the subsequent media frenzy was seemingly disproportionate to the threat, the author concludes, excessive media coverage of the panic served as a proxy (subtext) for expressing white Canadian anxieties over the growing presence (and perceived menace) of racialized minorities. Clearly, then, remains a key organizational principle in framing reality along the lines of what is normal, acceptable, and desirable. After all, over-the-top reaction to the nonEbola case could resonate meaningfully only with a racialized audience already inured to/by race-logic for making sense of the world (13). The implications of this subliminal yet racialized coverage are consistent with what Frances Henry and Carole Tator call democratic racism--a uniquely Canadian racism that thrives on exploiting the contradiction between Canada's ideals of inequality and the reality of racialized inequality. …
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 | 0,002 |
| 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 | 0,000 | 0,000 |
| 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 ».