Global Consumption from the Perspective of Population Health
Notice bibliographique
Résumé
Can wealthy societies maintain their health status while consuming less of the world's resources? This may seem like an esoteric question, yet Canada has recently ratified the Kyoto Accord. In order to meet its commitments under the Accord, Canada will need to reduce emissions of carbon dioxide by approximately 20% over the next decade. Since carbon dioxide is the end product of consumption of resources the question is de facto irresistible. In the modern world, health, wealth, and consumption tend to occur together. Increasing per capita income among countries tends to be associated with increasing longevity. Early in this century the relationship was simple: life expectancy was longer in countries with higher per capita incomes. However, in recent decades the relationship between health and wealth has become more complex as nations have grown richer. The specific character of this complexity forms a basis for a more encouraging answer to the question posed above. When longevity and national income curves are plotted together on a single graph, the cause for optimism can be seen in the changing character of the curves throughout the twentieth century. Figure 1 shows that, in 1900, the relationship between increasing national health and wealth was nearly linear. Wealthier meant healthier. But throughout the twentieth century the strength of this association increasingly broke down. By 1960, the slope of the health-wealth had flattened at the rich end, such that variations in national income per capita were no longer strongly associated with further increases in life expectancy. By 1990 all the world's wealthiest nations (those belonging to the Organization of Economic Cooperation and Development) found themselves on this of the curve (World Bank 1993). At the same time, the traditional monotonic relationship between health and wealth persisted among the world's poorer countries; a pattern referred to here as the steep incline, to distinguish it from the of the curve. [FIGURE 1 OMITTED] There are several ways to interpret these trends. One of the simplest is to assert that the material factors that limit health status in poor societies, such as food, clothing, shelter and clean water, become relatively unimportant determinants of health when national income reaches a certain level. This is intuitively appealing because there is such a thing as a sufficient amount of food, clothing, shelter, and clean water, beyond which further consumption should not lead to further health benefit. It may be pleasant to have better food, clothing and shelter, but they would not necessarily confer additional health benefits. One simple conclusion, from the standpoint of economic development and health, is that poorer countries' attempting to match the rich, and reach the flat of the curve, is an essentially benign objective. In other words, the relationship between healthy and wealthy countries and poor and unhealthy countries ought to be one of imitation of the former by the latter. This interpretation assumes that economic growth, traditionally defined, is a laudable objective regardless of the forms that it takes. But this view is challenged by evidence that shows how differently and poor nations appropriate global photosynthetic resources. This is best represented in the calculation of the ecological footprint, which is a measure of the area of the Earth's surface appropriated for its use by a given population in a given year (Wackernagel 1995). Consumption of ecologically productive land (that is, land appropriated for energy, agriculture, and forest products as well as the area of the built environment per se) has grown rapidly across the globe in recent decades. Between 1950 and 1990, the appropriation of ecologically productive land by the worlds' richest countries increased from approximately 2 hectares to between 4 and 6 hectares per capita. …
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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 ».