Evaluating materiality disclosure in sustainability reports: A study of North American construction and engineering firms
Bibliographic record
Abstract
This research evaluates the sustainability reporting practices of 10 leading North American con-struction and engineering firms, focusing on adherence to the Sustainability Accounting Standards Board (SASB) Standards for the Engineering and Construction Services sector. The analysis covers five material topics: Ecological Impacts, Product Quality & Safety, Employee Health & Safety, Prod-uct Design & Lifecycle Management, and Business Ethics. Results reveal significant gaps in report-ing, with most firms failing to meet full disclosure for SASB metrics. Ecological Impacts and Business Ethics are the weakest areas, with limited disclosures on environmental risks and anti-competitive practices. Employee Health & Safety shows moderate compliance, with few firms reporting key metrics like Total Recordable Incident Rates (TRIR). The study highlights the urgent need for en-hanced transparency, standardized reporting, and robust governance frameworks. Improving alignment with SASB standards will foster accountability, strengthen stakeholder trust, and ad-vance sustainability within the sector.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".