Who is getting the public goods in India: Some evidence
Notice bibliographique
Résumé
The way you grow up in India, it has long been known, depends on where you grow up. The average child growing up in Orissa in the 1980s was seven times more likely to die in infancy than his or her equivalent in Kerala. 2 His or her mother is four and half times more likely to die in giving birth if she were in Assam than she would be had she been in Kerala. 3 And if she happens to be a girl and born in Rajasthan in the 1980s, the likelihood of her being literate by the time she was 14 was about a quarter of what it would have been had she grown up in Kerala. 4 This is, as Dreze and Sen (1995), among others, have argued is entirely what we might have expected: In 1991, rural Kerala had 17 times as many hospital beds per head as Orissa and 10 times as many as Assam. The fraction of people in rural Orissa with access to medical facilities in their village in 1981 was less than 11 % compared to 96 % in Kerala. In 1991, 93 % of villages in Kerala had a middle school but the corresponding fraction in Orissa and Assam was less than 25 % and in UP it was less than 15%. What is less often emphasized but equally striking is the extent of variation within a single state: According to the 1991 census, less than 7 % of the villages in Vishakhapatnam district in Andhra Pradesh had middle schools and just over 46 % had some educational facility, as against 55 % and 100 % in Guntur. The district of Rangareddy had only 6 % of villages with primary health sub-centers as against almost 40 % in Anantapur. Less than 1 % of villages in Vishakhapatnam had tapped water compared to 59 % in West Godavari. Forty-eight percent of villages in Vishakhapatnam were using electrical power as against essentially 100 % in Krishna. Twenty percent of 1 I am grateful to Pranab Bardhan, Kaushik Basu and Maitreesh Ghatak for helpful comments. I also wish to thank, without implicating in any way, Lakshmi Iyer and Rohini Somanathan for their ongoing collaboration in the research that lies behind this paper. 2 Based on the 1991 census.
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 | 0,008 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,012 |
| Études des sciences et des technologies | 0,002 | 0,007 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,002 |
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 ».