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Record W3212792426 · doi:10.5539/eer.v11n2p54

Payment for Environmental Services for Waste Pickers: Systematic Literature Mapping

2021· article· en· W3212792426 on OpenAlexvenueno aff
Pollyana Ferreira da Silva, Gina Rizpah Besen, Helena Margarida Ribeiro

Bibliographic record

VenueEnergy and Environment Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
FundersUniversidade de São PauloCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPaymentProcurementWork (physics)BusinessService (business)Theme (computing)Systematic reviewQualitative researchService providerEnvironmental resource managementEnvironmental planningMarketingComputer scienceFinanceEnvironmental scienceSociologyEngineeringMEDLINE

Abstract

fetched live from OpenAlex

In Payment for Environmental Services (PES) systems, environmental service providers receive compensation for a conservationist action that implies the preservation of natural resources. The objective of this systematic mapping was to identify and discuss scientific articles that address the theme 'Payment for Environmental Services - PES for Waste Pickers Organizations', to understand the state of art of hiring these workers as environmental service providers. The study was developed using the method of systematic mapping of literature, from 2009 to 2019, considering qualitative and quantitative aspects. Results indicated that the countries that most investigate this theme are Brazil, China, India, and Indonesia. The articles portray the informal work of waste pickers, working conditions and the transition from informal systems to waste management in public services. The relationship between payment for environmental services and the work of waste pickers is not yet evident. Furthermore, research on PES and recycling are developed along distinct lines, without interdisciplinarity. However, PES shows itself as an important socio-environmental management tool that has the potential to solve relevant problems of recyclable waste management, because it presents congruent characteristics with the public procurement systems for waste pickers.

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.

How this classification was reachedexpand

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)0.001
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: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.267
Teacher spread0.239 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

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