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Record W3185317081 · doi:10.22215/etd/2021-14554

Participation in Sustainability Transitions: A Case Study of Engagement in Ottawa’s Energy Evolution Strategy

2021· dissertation· en· W3185317081 on OpenAlexaffabout
Daniel Atlas

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsCitizen journalismDemocracySustainabilityEcological modernizationSociologyState (computer science)Energy (signal processing)Political scienceEnergy transitionPublic administrationEcologyPolitics

Abstract

fetched live from OpenAlex

This thesis engages with the issue of how cities are responding to the challenge of climate change through participatory processes intended to enable sustainable energy transitions.It focuses on municipal-level energy transition planning in the city of Ottawa, Ontario Canada, using a case study of participation in Ottawa's Energy Evolution Strategy.This Strategy aims to have the city reach net-zero greenhouse gas emissions by 2050.This thesis draws on 14 semi-structured interviews with Energy Evolution participants and city staff as well as other primary sources such as reports and meeting minutes.It examines democratic engagement in Energy Evolution informed by two theoretical frames which, together, provide a holistic view of participation in sustainability transitions.Constructivist science and technology studies (STS) theory is used to analyze the creation of the participatory process.Informed by STS theory, I show that Energy Evolution was purposefully created and only partially framed as participatory.It was stakeholder focused, invited, professionally facilitated, and maintained a technocratic focus on energy transitions.I also assess the process against specific normative criteria, informed by the theory of ecological democracy.I show that Energy Evolution was only partly participatory in the way that is envisioned by ecological democracy theorists.Informed by this analysis, I argue for the increased role of diverse non-state actors in transitions processes, noting that for such processes to be effective, these actors require a deeper understanding of, and influence on, participatory processes in institutional spaces that are empowered to make these important environmental decisions.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0350.017
Scholarly communication0.0060.003
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.314
Teacher spread0.290 · 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 designQualitative
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

Citations0
Published2021
Admission routes2
Has abstractyes

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Same topicSustainability and Climate Change GovernanceFrench-language works237,207