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The problem with net zero building policy: reflecting on the making, and future, of a global discourse

2023· article· en· W4382139804 on OpenAlexaff
Lisa N. Hasan, Gonzalo Lizarralde, Érick Lachapelle

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2023
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsUniversité de MontréalHEC Montréal
Fundersnot available
KeywordsLegitimationLegitimacyZero (linguistics)Corporate governanceZero-energy buildingReputationGlobal governanceValue (mathematics)Net (polyhedron)Political scienceBusinessEconomic systemPublic relationsPolitical economySociologyEconomicsEngineeringComputer scienceLawPoliticsEfficient energy useMathematics

Abstract

fetched live from OpenAlex

Abstract The Paris Agreement made net zero emissions a global target. In response, net zero carbon building standards have proliferated, making net zero a popular target for buildings. But to meaningfully contribute to global decarbonization efforts, net zero standards and the organizations who promote them, must be deemed legitimate. Given the building industry’s reputation for being highly fragmented and slow to change, how has this legitimacy been constructed? What are the implications of this legitimation process? This article seeks to answer these questions by exploring the narratives used by the World Green Building Council (WGBC) to legitimate Net Zero Carbon Buildings (NZCB) from 2015 to 2021. Our analysis is based on over 100 documents produced by the WGBC and 22 interviews with WGBC and Green Building Council representatives, policymakers, and industry actors. Results reveal six main storylines adopted by the WGBC to extend the legitimacy of sustainable green building movement actors to the new net zero governance space. This legitimation process allows the WGBC to develop and implement net zero standards quickly, but also creates tensions between efficiency and procedural integrity, potential and proven results, corporate and collective value. While NZCB are here to stay, these tensions highlight barriers to their wide-scale adoption and question their ability to deliver an economically viable, socially just, environmental, net zero transition.

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)0.000
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 score0.592
Threshold uncertainty score0.408

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 studies0.0010.001
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 head0.016
GPT teacher head0.270
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

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 designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

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