THE WORLD BANK: GLOBAL HEALTH OR GLOBAL HARM?
Notice bibliographique
Résumé
In recent years the World Bank has become “the world’s largest external funder of health.”1(p61) According to Ruger, this situation reflects the Bank’s increased sensitivity to poverty and its growing sophistication—beginning under the leadership of US Secretary of Defense turned World Bank President (1968–1981) Robert McNamara—about development theory and practice. Such an uncritical portrayal befits the World Bank’s own Web site (a major source for Ruger’s article), but Journal readers should expect more. Missing from this officialist version are discussions of the Bank’s undemocratic governance and decisionmaking structures; the untoward human effects of longstanding World Bank pro-privatization policies and practices, most notably structural adjustment programs (which have denuded the social welfare infrastructure of developing countries in areas such as housing, education, health services, subsidies, and family transfers); and the impact on health of the Bank’s newfound focus on the health sector. Ruger repeats the insider’s lament that lending policies were perennially subject to the exigencies of Wall Street bondholders, but she overlooks the far larger question of the nature and distribution of power at the World Bank. With votes directly related to shareholding size, World Bank decision-making is profoundly undemocratic, favoring elite interests within wealthy nations (the United States alone commands 16.4% of votes within the Bank). Any account of the Bank’s evolution ought to consider the impact of this governance structure on the roles and activities that the Bank adopts. According to both internal and external observers, the neoliberal policies advocated by the Bank and its sister institutions beginning in the 1980s have provoked or worsened dire economic conditions—and the attendant health effects, such as increased rates of malaria, HIV/AIDS, and tuberculosis—in much of the developing world.2–5 This “role of the World Bank in global health” remains unaddressed by Ruger. Indeed, the negative impact of structural adjustment programs on health conditions in developing countries helped spur the Bank’s focus on health in the late 1980s.6 With its double-entendre title, the Bank’s influential 1993 report Investing in Health hailed the importance of health to development while advocating the privatization of health services.7 But the Bank’s approach to health sector lending has exacerbated poor health outcomes by reducing access to health services for those unable to pay for care in newly privatized systems, which focus on cost recovery.8,9 Recent targeted programs aimed at the poorest ignore structural deficiencies in social services. In sum, Ruger portrays the Bank’s increasing involvement in the health sector as un-problematic. Critics are dismissed as a handful of cranks rather than as serious academic and policy researchers.10–12 The author’s reliance on official Web sites and published histories rather than internal memos, archives, and interviews, to which a former speech-writer for the World Bank president might have sought access, is disappointing. In failing to convert the price tags of projects into inflation-adjusted dollars—a surprising oversight for a health economist—Ruger underestimates the impact of past World Bank activities. Overall, this one-sided article fails to elucidate the powerful political and economic forces motivating World Bank policies and activities and does not provide the carefully researched historical analysis we have come to expect from “Public Health Then and Now” articles.
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 | 0,007 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,012 |
| Communication savante | 0,014 | 0,017 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,010 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,043 | 0,013 |
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 ».