Development of an Indicator-Based Framework for a Sustainable Building Retrofit
Bibliographic record
Abstract
This study develops and operationalizes a multi-dimensional framework for sustainable building retrofit that aligns with national 2050 net-zero objectives. First, we conduct a scoping review of international standards (e.g., ISO), sustainability reporting guidelines (GRI G4), and peer-reviewed studies to define an indicator system spanning three pillars—environmental (carbon neutrality, resource circulation, pollution management), social (habitability, durability/safety, regional impact), and economic (direct support, deregulation). Building on this structure, we propose a transparent 0–3 rubric at the sub-indicator level and introduce the Sustainable Building Retrofit Index (SRI) to enable cross-case comparability and over-time monitoring. We then apply the framework to seven countries (United States, Canada, United Kingdom, France, Germany, Japan, and South Korea), score their retrofit systems/policies, and synthesize results through radar plots and a composite SRI. The analysis shows broad emphasis on carbon neutrality and habitability but persistent gaps in resource circulation, pollution management, regional impacts, and deregulatory mechanisms. For South Korea, policies remain energy-centric, with relatively limited treatment of resource/pollution issues and place-based social outcomes; economic instruments predominantly favor direct financial support. To address these gaps, we propose (i) life-cycle assessment (LCA)–based reporting that covers greenhouse gas and six additional impact categories for retrofit projects; (ii) a support program requiring community and ecosystem-impact reporting with performance-linked incentives; and (iii) targeted deregulation to reduce uptake barriers. The paper’s novelty lies in translating diffuse sustainability principles into a replicable, quantitative index (SRI) that supports benchmarking, policy revision, and longitudinal tracking across jurisdictions. The framework offers actionable guidance for policymakers and a foundation for future extensions (e.g., additional countries, legal/municipal instruments, refined weights).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.025 | 0.016 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".