Framework for integrating sustainability into remediation projects
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 The US Sustainable Remediation Forum (SURF) created this Framework to enable sustainability parameters to be integrated and balanced throughout the remediation project life cycle, while ensuring long‐term protection of human health and the environment and achieving public and regulatory acceptance. Parameters are considerations, impacts, or stressors of environmental, social, and economic importance. Because remediation project phases are not stand‐alone entities but interconnected components of the wider remediation system, the Framework provides a systematic, process‐based approach in which sustainability is integrated holistically and iteratively within the wider remediation system. By focusing stakeholders on the preferred end use or future use of a site at the beginning of a remediation project, the Framework helps stakeholders form a disciplined planning strategy. Specifically, the Framework is designed to help remediation practitioners (1) perform a tiered sustainability evaluation, (2) update the conceptual site model based on the results of the sustainability evaluation, (3) identify and implement sustainability impact measures, and (4) balance sustainability and other considerations during the remediation decision‐making process. The result is a process that encourages communication among different stakeholders and allows remediation practitioners to achieve regulatory goals and maximize the integration of sustainability parameters during the remediation process. © 2011 Wiley Periodicals, Inc.
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 | 0.006 |
| 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 | 0.001 |
| 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