Multi-Sectoral Partnership for Waste Management Evaluation and Awards Recognition in Higher Education
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
Waste management is an important part to achieve green and sustainable campus. This study aims to evaluate waste management implementation in higher education. The methodology used in this study is a cross sectional with a non-probabilistic sampling. Data were collected using a well-structured evaluation instrument through an online focus group discussion, document review and evidence of implementation. The evaluation instrument consists of 10 elements: waste management policy, resource availability, waste segregation, waste collection, temporary waste storage, handling of general and hazardous waste, personal protective equipment (PPE), waste segregation awareness educational program, and evaluation on waste management. There were 15 faculties/schools/program were participated. Data was analysed using univariate analysis, radar plot representation, Box and Whiskers plot analysis. The level of waste management implementation amongst faculties /schools/program was varied between 52% to 98%. Higher education needs to evaluate waste management implementation and established a systematic environmental awareness program to achieve sustainability development goals (SDGs). The mean score ranking from highest to lowest level: personal protective equipment (5.6) to evaluation of waste management implementation (3.2). Indeed, to ensure a comprehensive general waste management, it was suggested that higher education need to build a centralized waste collection facility, a chemical waste treatment and competence personnel for handling laboratory waste.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it