Enhancing environmental, social, and governance, performance and reporting through integration of life cycle sustainability assessment framework
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
Abstract We introduce an innovative framework integrating Life Cycle Sustainability Assessment (LCSA) impact categories with Environmental, Social, and Governance (ESG) factors, offering a unified approach for ESG assessment and reporting. It covers sustainable development's key aspects, enabling a detailed evaluation of environmental, economic, and social performance across product and system life cycles, in line with the Sustainable Development Goals (SDGs). Incorporating the UN's 10 principles, the framework fosters a synergy to improve ESG reporting, adaptable across industries. To demonstrate its practicality, a theoretical application in Canada's oil and gas sector highlights how this framework can provide actionable insights for SDG‐aligned performance improvements. This example illustrates how the framework can identify and address sustainability issues, thereby improving ESG performance. Beyond its theoretical contributions, the framework serves as a valuable tool for practitioners and investors, promoting informed and comprehensive ESG reporting. Ultimately, it aims to enhance organizations' contributions towards achieving the SDGs and advancing global sustainability.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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