The Wa-Pa-Su Project Sustainability Rating System: A Simulated Case Study of Implementation and Sustainability Assessment
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
Large-scale projects create a variety of social, economic, and environmental impacts throughout their life cycles. Assessing sustainable development becomes a measurable factor, not only for the organizations directly involved in the development, construction, and operation of projects, but also for a number of other stakeholders. In the oil sands and in heavy oil operations, assessment turns into a periodical task, since the construction and operation phases of the projects can last for a considerable period of time. The sustainability assessment tool must have the capability for the organizations and/or projects to evaluate and improve performance over time. The Wa-Pa-Su project sustainability rating system’s design and characteristics meet the sustainability assessment needs of the oil sands and heavy oil operations; therefore, the development of its structure is based to support each area of operation (i.e., sub-divisions) and address the diverse impacts (i.e., areas of excellence) in each pillar of sustainability (i.e., social, economic, and environmental). Though the different sustainable development indicators (SDIs) are incorporated with the aim of measuring the sustainable development of the oil sands projects, the assessment methodology used for measuring sustainability can be implemented in a large range of projects and organizations due to its integrated approach. Since the Wa-Pa-Su project sustainability rating system is the first of its kind focusing on industrial projects with an emphasis in oil sands and heavy oil, it must be understood that a variety of SDIs have not yet been measured, and the data required for this purpose have not been collected; therefore, the objective of this paper is to highlight the flexibility and applicability of the rating system by presenting a simulated case study of implementation and sustainability assessment using an integrated approach.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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