Framework for Assessing the Sustainability of Innovative Building Technology
Bibliographic record
Abstract
The construction industry faces the dual challenge of providing affordable housing while addressing the pressing issue of climate change. In South Africa, many residents are forced to live in informal settlements due to a lack of affordable housing. This study aims to develop a sustainability assessment framework that evaluates the interconnectedness of affordability, social sustainability and environmental impact. The framework emphasizes the importance of reducing greenhouse gas emissions. It incorporates energy consumption and socio-economic impact criteria aligning with the United Nations Sustainable Development Goals (SDGs). The findings suggest that while sustainable building practices may incur higher initial costs, they offer long-term benefits, including reduced energy consumption and carbon emissions. The proposed framework will serve as a tool for evaluating the sustainability of innovative building technologies, contributing to the discourse on sustainable construction practices. The study recommends an enhanced stakeholder engagement and a regulatory landscape conducive to adopting IBTs. Further empirical research is recommended to refine the framework and broaden its applicability across different contexts.
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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 | 0.017 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.012 | 0.005 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".