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Solid Waste Management in Chennai: Lessons from Exnora

2016· article· en· W2735646247 sur OpenAlexvenueno aff
Niyati Mahajan

Notice bibliographique

Revue˜The œinnovation journal · 2016
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueUrban and Rural Development Challenges
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMunicipal solid wasteGarbagePer capitaBusinessWaste disposalMegacityPopulationWaste collectionMunicipal corporationLocal governmentWaste managementEnvironmental planningAgricultural economicsEngineeringGeographyEconomicsEconomyEnvironmental health
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

IntroductionIn Indian megacities, municipal solid waste management has become a challenging problem, especially in cities like Chennai, which generates 0.71 kg of municipal solid waste per capita every day-the highest in the country (Chennai's per capita waste at 0.7 kg highest in the country, 2014). Growing waste generation is mainly due to population growth, economic development and changing lifestyles. Primarily responsible for waste management, municipalities and local agencies have been ineffective in tackling the waste problem. Some issues related to municipal solid waste management are low priority for safe disposal, lack of appropriate organization, insufficient financial and technical resources, a limited number of disposal sites and inadequate knowledge of disposal methodology (Pandian, Ramanathan and Rawat, 2010: 199).Municipal solid waste is simply collected, transported and dumped without treatment or processing. A substantial amount of waste remains unattended at collection centers, roadsides and riverbanks. Most often cows and other stray animals feed on waste dumped in these places. Open dumping of garbage facilitates the breeding of disease vectors and unsanitary dumpsites increase the risk of groundwater contamination (Kumar, Venkata and Rao, 2013: 48). Asubstantial amount ofthe municipal waste budget (around 75 per cent) is spent on street sweeping, with only 20 per cent on transportation and 5 per cent or less on disposal (Hanrahan, Srivastava and Ramakrishna, 2006: 30). However, in spite of street sweeping, roads remain dirty, spoiling the aesthetic beauty of cities and towns. It is common to see people throw their rubbish onto the street. The prevailing thought is cleaning up is always somebody else's responsibility. The Government of India issued Municipal Solid Waste (Management and Handling) Rules, 2000 to improve waste management. The rules promised environmental sustainability in solid waste management by promoting waste separation, recycling, and use of disposal techniques such as composting and incineration. Government agencies believed privatization to be the panacea for solid waste problems. Under the impetus of Municipal Solid Waste Rules and the privatization drive, Chennai became first city to contract out municipal solid waste management services to a foreign agency, the French company Onyx (Ahluwalia, Kanbur and Mohanty, 2014: 225); however, in spite of the Municipal Solid Waste Rules, the Greater Chennai Corporation1 and the private operators continued to dispose of the collected mixed waste at open dumpsites, posing ongoing risks to the environment and public health (CMDA, 2008).Besides Greater Chennai Corporation and private operators, non-government organizations such as Exnora are also working as conservancy agencies2 3 in the field of solid waste management. Exnora introduced the concept of people participation in solid waste management by forming community-based organizations such as Civic Exnora to independently manage waste in their locality, with the parent body playing an advisory role (Dhamija, 2006: 84). The Civic Exnora innovation has shown that the active participation of people can bring a spark of change. Exnora is active in Chennai, Panipat, Lucknow and Hyderabad, but this paper mainly focuses on Exnora in Chennai. A non-government organization, Civic Exnora provides sustainable waste management systems that are successful in reducing waste and generating employment and income. The community intervention Exnora, however, has a marginal presence and is vulnerable to indiscriminate privatization drives. With this background, this article seeks to understand how Exnora functions and to explore whether Civic Exnora has and to what extent could in the future keep the streets free from garbage and assist rag pickers in spite of the challenges from political pressures and growing privatization.A review of existing literature reveals that several studies on Exnora have been undertaken. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,624
Score d'incertitude au seuil0,596

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,064
Tête enseignante GPT0,343
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2016
Routes d'admission1
Résumé présentoui

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