Sustainable Management Practice (SMP) of Green Features in Office Property in Lagos, Nigeria
Bibliographic record
Abstract
In this study, we examine the adoption of sustainable management practice (SMP) for green features in an office building using Lagos office property as a case study. The opinion of the professional property managers was sampled, and their responses were analyzed by weighted mean score (WMS), one simple test statistic (t-stats), severity index (S.I.), and factor analysis model. The study discovered that while energy-efficient related green features were the most incorporated, property managers often manage the efficient use of spaces among other green features in the office property. The property managers are yet to fully adopt the SMP, but sustainable resource management and repair and replacement maintenance management were highly considered among the SMP. The challenges of SMP were categorized into three broad barriers: GB project cost/finance, economic/market expectation, and professionalism/institutional barriers. We concluded that the country's property managers are yet to adopt SMP fully. We recommended the integrated GB practice advocacy, encouragement of strong institutional backing for developing the country's GB rating tools, and professionalism for SMP to thrive in the country.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".