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How can CASBEE contribute as a sustainability assessment tool to achieve the SDGs?

2019· article· en· W2968958318 on OpenAlex
G Miyazaki, Shun Kawakubo, Shuzo Murakami, Toshiharu Ikaga

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.

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsSustainabilitySustainable developmentScale (ratio)Environmental planningEnvironmental resource managementEnvironmental economicsBusinessGeographyPolitical scienceEnvironmental scienceEconomicsCartography

Abstract

fetched live from OpenAlex

Abstract The purpose of this research was to understand the relationship between assessment items of the Comprehensive Assessment System for Built Environment Efficiency (CASBEE) and the UN’s Sustainable Development Goals (SDGs). The SDGs, the core of the 2030 Agenda for Sustainable Development, were adopted in 2015. In response, social demand for sustainable buildings, urban districts, and cities has grown. New assessment tools have been developed to quantitatively evaluate the sustainability of individual buildings, building clusters, urban districts, and cities worldwide. CASBEE was developed in Japan, with assessment items suited to each scale, from individual buildings to entire cities. These assessment items are expected to contribute to SDG 11 “Sustainable Cities and Communities” as well as the other 16 goals. However, the degree of correspondence between assessment items and SDGs remains unclear. Therefore, the relationships between CASBEE assessment items and SDGs were investigated to confirm their effectiveness as a tool for sustainable design. In this analysis, the number of corresponding goals increased as the scale became broader. At the scales of individual buildings and building clusters, many assessment items contributed indirectly to SDG 12 “Responsible Consumption and Production” while many assessment items contributed directly to SDG 11 in urban districts and cities.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.668

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 studies0.0000.001
Scholarly communication0.0010.001
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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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