An Integrated Fuzzy-Based Sustainability Framework for Post-Secondary Educational Buildings: A User-Perspective Approach
Bibliographic record
Abstract
Decreasing the impact of educational buildings on the environment is a primary concern of the sustainable building movement. However, limited research has centered on improving educational building sustainability from users’ perspectives. This study aims to determine an overall user perspective satisfaction scale (OUPS) for post-secondary educational buildings, determine the factors and sub-factors that affect users’ perspectives, and create a building sustainability platform for evaluating user satisfaction. The main goal of the developed model is to offer facility managers the current users’ perspectives on post-secondary educational buildings to improve sustainability from users’ perspectives. The results revealed a significant influence of thermal comfort (40%) and aesthetics (22%) on users’ perspectives. The developed model was validated by experts working in the facility management field and they acknowledged it as having good potential. This work first utilized the Fuzzy Analytic Network Process (FANP) modelling technique to determine weights for each factor and sub-factor and then employed the fuzzy expert system to develop an OUPS. Questionnaire responses and interviews with facility managers and users were used to develop these models for a case study of the M.B. building at Concordia University in Montreal, Quebec.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".