A systematic review of managing sustainable construction projects: Insights from education, innovation, and governance
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
There is abundant literature on sustainable construction projects. This review study collects a set of studies to understand the depth of the topic as per the Sustainable Development Goals (SDGs). For this purpose, the Scopus database is explored with a systematic review approach, and 80 studies are selected. The literature emphasizes the integration of human capital, technological innovation, governance, and financial support to achieve sustainable objectives in construction projects. Moreover, education can improve technical and strategic competencies in graduates to promote experiential learning for the construction industry. Furthermore, sustainable construction can be enhanced by circular economy principles. In addition, risk management also needs attention to ensure operational reliability in construction projects. For this purpose, institutions and governance can align technical and ecological priorities in a project to achieve sustainability objectives. Innovations can also improve efficiency and knowledge management. Lastly, economic and financial mechanisms can also support this phenomenon. The study suggests promoting education, technology, and governance to support sustainable construction as per the SDGs.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it