Sustainable or Green Construction in Lagos, Nigeria: Principles, Attributes and Framework
Bibliographic record
Abstract
The concept of sustainable development is used as a basis for enhancing understanding of sustainable construction. Principles of sustainable construction cover four attributes: social, economic, biophysical and technical. The research examined these concepts, principles and attributes in understanding sustainable and green construction as well as current practices and challenges of sustainable construction in Lagos, Nigeria. The research embraced both quantitative and qualitative methods of data collection. The sample frame is the total number of built industry registered and practising professionals in Lagos. A total number of 85 respondents were randomly selected for study from each group. A 5-point likert scale was used to assess respondents’ judgement on the identified social, economic, bio-physical and technical indicators. Focus group discussions (FGDs) were also conducted with all the above professional groups to corroborate the primary information. For a wider coverage, three different construction sites are selected to reflect income neighbourhoods-Lekki (high income), Yaba (medium income) and Bariga (low income). Data Collected were analysed using the mean item score. A multi- stage framework which required the application of environmental assessment and environment management systems for construction projects was utilised. Research findings indicate that the most important factors considered for sustainable construction with their mean item scores are quality of working conditions (0.852) strengthening and enforcement of relevant law and regulations(0.872), encouraging construction waste management(0.819) and design for flexibility and adaptability. Results from the FGDs indicate that the current practice on sustainable construction does not take into consideration integrated design process, acoustic and visual comfort in the planning and construction of sustainable projects. The research therefore concludes that government should improve existing laws to enhance quality of working life, education, training as well as knowledge management for all stakeholders in sustainable construction.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".