Mind the Gap: An Evaluation of Indicator Discrepancies between Sustainability Standards and Certifications in the Built Asset Industry
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.
Bibliographic record
Abstract
The built asset industry impacts our global environment significantly, contributing notably to environmental degradation. Various sustainability standards and certifications, such as LEED, DGNB, BREEAM, ISO 14001, and GRI 200 series, have been established to guide the industry toward sustainable practices. Despite their intended purpose, the diversity of these systems has led to a complex and inconsistent landscape. This paper undertakes a review of 25 certifications and 26 standards in the built asset industry, identifying and analyzing gaps and discrepancies in their measuring indicators. Using a rigorous process, we consolidated the diverse measuring indicators from each scheme into a list of 189 specific indicators, for comparative analysis. This analysis revealed notable gaps and inconsistencies within these schemes, illuminating differences in their emphasis and coverage of sustainability indicators. These findings highlight the need for increased standardization and inclusiveness in sustainability assessments within the industry. This study contributes to the discourse on industry standardization, policy decisions, sector transparency, and further research, marking a crucial step towards a more integrated approach to sustainability in the built asset industry. Keywords: Sustainability, built asset industry, Sustainability standards, Green Building Certification
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it