Notice bibliographique
Résumé
Location matters. The most striking example is the highly uneven distribution of population and wealth across space. For example, cities occupy approximately 2 percent of the Earth’s land surface, but host more than half of the world’s population and produce about 80 percent of its economic output. The twenty most populous US metropolitan statistical areas (MSAs) account for almost 45 percent of the total US population and produce 52.2 percent of total US GDP on barely 15.2 percent of total US surface. Similar patterns hold for other countries, with even starker concentrations of population and economic activity in the growing megalopolises of developing countries. This entry discusses why population and economic activity are not more evenly spread across space. The first reason that comes to mind is that places are intrinsically heterogeneous along different dimensions such as topography, resource endowments, access to natural transportation routes, or climate. More importantly, what makes a location desirable to an agent is the unintended byproduct of the other agents’ location choices: everyone cares about her own position, but the actual choice is relative to those of the others. To put it differently, the desirability of a specific location depends on where the others are located. This simple fact is the essence of spatial equilibrium, a formal concept used by economists to analyze the spatial distribution of economic agents and activity. It describes a situation where each economic agent optimally chooses her own location—taking the locations of the others as given—and where these interdependent location choices are mutually compatible. The outcome is determined by the interplay between two sets of competing forces. First, everything else equal, agents want to be close together (“agglomeration forces”). This comes from the fact that moving people, goods, and ideas across space is costly, which pushes toward geographic concentration to reduce these costs and increase the benefits generated by clustering. Second, everything else equal, there are limits to geographic concentration at any point in space, which tends to push agents apart (“dispersion forces”). The main limits to agglomeration lie in competition for land, which is an immobile good in (more or less) limited supply, and different other negatives—congestion, noise, pollution—that increase with geographic concentration. Because only a limited number of agents can be spatially close to each other, most interactions occur across distant locations and are, therefore, costly. Each agent trades off the benefits generated by the agglomeration forces and the costs generated by the dispersion forces to choose his or her own location, which depends on where the others are located. The resulting spatial equilibrium is the outcome of these interdependent optimization processes carried out by economic agents who pursue their own interests.
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 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,010 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».