THE EFFECTIVENESS OF BOMA BESt AND LEED CANADA EB:O&M IN GREENING COMMERCIAL BUILDINGS
Bibliographic record
Abstract
LEED Canada for Existing Buildings: Operations and Maintenance (LEED Canada EB:O&M) and Building Owners and Managers Association's Building Environmental Standards (BOMA BESt) are complex green rating systems that offer owners, managers, consultants, and tenants distinct value propositions for existing buildings. Upon close examination, significant variations between the systems are evident in certification process, cost, rigor, engagement, marketing, accessibility, transparency, management, and program philosophy. Despite the many differences between the systems, they are often seen to be complementary programs and are sometimes used in tandem for the same building. This paper reports on a survey of the industry perceptions of the value and strengths of the LEED Canada EB:O&M and BOMA BESt rating systems with respect to the above criteria. As a result of the fundamentally different nature of the programs, preferences for LEED Canada EB:O&M and BOMA BESt are determined by stakeholder values and the programs are used for a variety of reasons.
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 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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".