Strengthening the Link between Life Cycle Assessment and Indicators for Absolute Sustainability To Support Development within Planetary Boundaries
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
THE INSUFFICIENCY OF ECO-EFFICIENCYLife cycle assessments (LCA) are increasingly used by industry to communicate improvements of environmental performance in a scientifically defendable way.Typically, studies compare new product designs with "last year's model" or a market reference to document that the eco-efficiency of a company's product portfolio is gradually improving or to show that the company is ahead of its competitors in terms of eco-efficiency performance.In both cases the signal to stakeholders is that companies are doing "their share" to foster sustainability.However, while the environmental performance of individual products is being improved, humanity is generally moving further away from a state of environmental sustainability. 1 The reason for this seeming contradiction is that improvements in eco-efficiency are insufficient to offset increasing levels of consumption.For example, PricewaterhouseCoopers calculated that the global eco-efficiency improvement from 2000 to 2013 with respect to greenhouse gas (GHG) emissions of 0.9% per year needs to increase to 6.2% per year and remain at that level until the year 2100 for emission volumes to be aligned with IPCC's RCP2.6 scenario.In other words, the recent decarbonization rate of the global economy must increase by a factor of 7 to avoid exceeding a global temperature increase of 2 °C. 2 How
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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