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Record W1651778713 · doi:10.1111/1759-5436.12140

Private Sector and Waste Management in Delhi: A Political Economy Perspective

2015· article· en· W1651778713 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIDS Bulletin · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsPerspective (graphical)PoliticsCommonsPrivate sectorInformal sectorOpenAccessNew delhiBusinessEconomic systemEconomyPolitical scienceEconomic growthPolitical economyLivelihoodEconomicsGeography

Abstract

fetched live from OpenAlex

Due to their size and rapid growth, large cities in developing countries are increasingly challenged by burgeoning waste generation. Waste management, however, has traditionally provided employment opportunities to the many urban poor in the informal sector. These traditional models, working largely in parallel with state?led interventions, are under pressure because they fail to address the waste management crisis. This failure, coupled with the lack of capacities of local governments, has paved the way for formal private sector participation. We examine the case of Delhi where a complex interplay of competing approaches have accompanied efforts of urban local bodies, civil society and the private sector (informal and formal) at finding a sustainable working solution. Our analysis of the complex relationship within the private sector players, and between private and public actors, provides novel insights into potential contribution of public–private partnerships for effective waste management in developing countries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.278
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it