Creating a ‘sustainability sublime’ to enable megaprojects to meet the United Nations sustainable development goals
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 Despite cost and schedule overruns and benefits shortfalls, megaprojects (which are large‐scale projects that typically cost over a billion dollars and take years to develop and build) continue to be promoted and built creating a megaproject paradox. Prominent megaproject scholar Bent Flyvbjerg (2014) argued that this could be motivated by four ‘sublimes’—technological, political, economic and aesthetic that drive new megaprojects being put forward despite their poor performance. Recent evidence shows that better governance practices are helping to improve the overall performance of megaprojects. Despite the United Nations setting 17 sustainable development goals (SDGs) to be achieved by 2030, there are severe shortfalls in initiatives from governments, public organizations and private businesses endangering the achievement of targets set for these goals. In addition, time is running out to achieve these goals with only a decade left. The current initiatives contributing to these goals appear to be focused on individual SDGs even though many of these are interrelated. This article proposes that if politicians, engineers and scientists, businesses leaders and design thinkers could be motivated by a ‘sustainability sublime’ to create megaprojects that contribute to SDGs, it could benefit both the society and the planet. It also argues that a more integrated view of UN SDGs and a suitable governance structure should be applied to ensure that megaprojects created as a result of the sustainability sublime deliver benefits towards achieving UN SDGs.
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 | 0.017 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.038 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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