From vaccine to visa apartheid, how anti-Blackness persists in global health
Notice bibliographique
Résumé
Global health evolved from colonial medicine and hence deeply rooted in the white supremacy mindset [1].Anti-Blackness is an inescapable consequence.Definitions of anti-Blackness revolve around the positioning of Black people, their cultural practices and knowledge as inferior, the conscious and unconscious dehumanization and discrimination of Black bodies, a disdain for Black people and their lived experiences, the disenfranchisement of Black people, but above all, a system of beliefs and practices that erode their humanity.In a recent event held in Nairobi, Kenya, we discussed what anti-Blackness in global health means, why it matters, and what needs to be done to counter anti-Blackness in global health and development [2]. How does anti-Blackness manifest itself?No continent has been more impacted by the ravages of colonialism and racism than the African continent.Sadly, even today, Africans are at the receiving end of discrimination, from vaccine apartheid to visa apartheid.The Covid-19 pandemic offers a stunning recent example of anti-Blackness.No continent is less vaccinated and boosted than the African continent [3].While wealthy nations rushed to clean up the shelves, hoard vaccines, and even throw away millions of expired vaccines, the African region was left last in the line.Despite the efforts of activists and the support of most countries, a few rich countries blocked the TRIPS waiver that could have significantly expanded vaccine manufacturing in the Global South.Two years after vaccination began in wealthy nations, and even as second and third booster shots are being offered in the Global North, barely one in four people in the African region are vaccinated with two doses (as of January 2023) [3].The African region has also had the lowest Covid-19 testing rate, and access to anti-viral medications such as Paxlovid is practically non-existent.This pattern of discrimination is not new.More than 30 years ago, when anti-retrovirals (ARV) became available, they were considered too expensive to roll-out in the African region.As late as 2001, some experts maintained that ARV treatment in Sub-Saharan Africa was impossible.It took incredible activism, legal action, and community effort before they started becoming available, by which time millions of Africans got infected and died.When the Ebola outbreak ravaged West Africa during 2014-16, it killed more than 11,000 people in Guinea, Liberia, and Sierra Leone.Even intravenous hydration was seen as being too challenging during this crisis.While an overwhelming majority of the mostly White American and European healthcare workers who contracted Ebola survived, the infection killed two-
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 | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,024 |
| Communication savante | 0,006 | 0,009 |
| Science ouverte | 0,000 | 0,005 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 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 ».