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Record W7108478865 · doi:10.5287/ora-pdng5r1z7

Jurisdictional approaches to reducing emissions from deforestation and forest degradation (REDD+) in Brazil

2022· dissertation· en· W7108478865 on OpenAlexaboutno aff

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsDeforestation (computer science)Context (archaeology)Climate changeGreenhouse gasReducing emissions from deforestation and forest degradationClimate change mitigationEmpirical researchMultidisciplinary approach

Abstract

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Delayed climate action from central governments has often prompted the engagement of subnational jurisdictions with climate policy. Given the burden environmental policies can appear to impose on different constituencies, why do subnational jurisdictions choose to adopt climate policies? What are the advantages and limitations of subnational climate action in the context of federal systems? How effective are subnational climate initiatives in curbing greenhouse gases (GHGs) emissions? These questions have been addressed by the literature in the context of developed countries, especially the United States, Canada, Australia, and European countries, but they remain under-investigated in the context of developing countries. My thesis contributes towards filling this gap by examining the pursuit of Jurisdictional Approaches (JAs) to Reducing Emissions from Deforestation and Forest Degradation (REDD+) by second-tier subnational jurisdictions in Brazil. Brazil is a developing country and a federation that provides a rich empirical context for studying the emergence of climate mitigation policies at the regional and local levels, and REDD+ has been a key policy tool embraced especially by states in Brazil. Understanding the limits to the authority of these second-tier jurisdictions, why and how some support certain climate policies while others do not, as well as how effective these policies are in contributing towards climate mitigation, is key to achieving the emissions reductions goals set by developing countries like Brazil. This research adopts a multi-method multidisciplinary and interdisciplinary approach organized around the analytical concept of the policy cycle, developed in the field of the Policy Sciences. The three empirical Chapters of the thesis (Chapters 4-6) consist of journal articles covering the stages of the policy cycles studied by each Chapter (agenda-setting, policy formulation, decision- making, implementation, and evaluation). The Chapters use a mix of qualitative and quantitative methodologies (comparative law, coding and text analysis, and econometrics techniques) and methods of data collection (court decisions’ selection and analysis, semi-structured interviews, and surveys) that resulted in three datasets (59 federal courts decision from the U.S. and Brazil, 46 transcribed semi- structured interviews, and 1,128 household surveys). These data and approaches were used to examine three key themes in the literature about the pursuit of JAs by subnational jurisdictions: (1) the authority of subnational jurisdictions to enact meaningful climate policies; (2) the internal and external incentives or the value proposition that motivated Brazilian states to adopt JAs to REDD+; and (3) the potential positive and negative interactions between JA interventions and existing policy frameworks already at play at the jurisdiction, and the challenges of coordinating the implementation of JAs and related policies across levels of governance. The findings and analysis put forward by this thesis contribute to the literature on the pursuit of JAs and other climate policies by second-tier jurisdictions by linking the extensive literature on subnational climate action in the U.S. to the more incipient discussions on the topic in Brazil, and by mapping the authority or the space for permissible action for Brazilian states pursuing climate policies in Chapter 4. In Chapter 5 the contribution is based the use of a novel analytical framework that examines both transnational and domestic factors to uncover what state-level policy actors in Brazil perceived the key incentives or value proposition to be for the adoption of JAs to REDD+. Finally, Chapter 6 offers new policy analysis that closely evaluates the impacts of early JAs and REDD+ project interventions and interactions with existing policy instruments in Brazil, linking the results to potential shortcomings in policy design and implementation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.053
GPT teacher head0.297
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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