Sustainability in geotechnical engineering: what does it mean and why does that matter?
Bibliographic record
Abstract
The aspiration to act in a more sustainable manner has become a guiding principle across many aspects of life. Yet sustainability is still often perceived as poorly defined, and there are diverse opinions on what the implications of sustainability for the everyday practice of geotechnical engineers are. Against this background, this paper presents a survey conducted at the Norwegian Geotechnical Institute at the beginning of 2021 that engaged a group of geotechnical engineers with the fundamental question as to how the concept of sustainability relates to geotechnical engineering. The Q methodology, a mixed-method approach, was applied to analyse different perspectives on sustainability in geotechnical engineering as inferred from the survey results. Three distinct perspectives were revealed that have a focus on (a) striving a balance between human action and nature, (b) mitigating the adverse impacts of geotechnical projects and (c) reducing resource use. Two of the perspectives considered the development of sustainability assessment tools as the most relevant means of working towards sustainable geotechnical practices, while the third perspective considered multidisciplinary collaboration and research as more important. Reflection on these perspectives can help the development of future tools and strategies, provide a direction for future research and contribute to a more sustainable geotechnical engineering practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".