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Record W4405829585 · doi:10.31025/2611-4135/2024.19433

SOLID WASTE POLICIES AND CLIMATE CHANGE – THE CASES OF FEDERAL BRAZIL AND CANADA

2024· article· en· W4405829585 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDetritus · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsClimate changeMunicipal solid wasteEnvironmental planningEnvironmental scienceBusinessWaste managementEngineeringGeologyOceanography

Abstract

fetched live from OpenAlex

The objective of our paper is to scrutinize the ongoing dynamics surrounding waste and climate policies within the federal democracies of Brazil and Canada. Our research design is guided by four primary inquiries. Firstly, we look at the integration of the circular economy concept within waste and climate policies. Secondly, we explore the extent to which concerns regarding solid waste are assimilated into climate mitigation and adaptation strategies. Thirdly, we assess the degree to which social inclusion is upheld as foundational principle within climate and waste policies. Lastly, we investigate the governance practices that have been put in place to promote effective intergovernmental and state-society cooperations. Initially, we illuminate the commonalities and disparities between Brazilian and Canadian federalism, emphasizing the challenges of policy coordination—a critical prerequisite for a smooth integration and successful execution of solid waste and climate policy initiatives. In the core section of our paper, we adopt a comparative lens to analyze both policy domains, focusing on (a) institutional frameworks, competencies, and the characteristics of the policy-making processes in each country; (b) legislative measures, programs, plans, and policy instruments to elucidate the policy fields and the linkages between them. We conclude our paper by juxtaposing the experiences of both countries and suggesting potential ways for mutual learning to improve federal democratic responses in tackling these complex and interlinked challenges.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.303

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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