The concept of value in sustainable infrastructure systems: a literature review
Bibliographic record
Abstract
Abstract Infrastructure choices and decisions widely employ the language of value, whether to articulate what is worthwhile or to debate which principles or approaches are most appropriate to specific contexts. As the world strives to achieve long-term sustainability goals, incorporating sustainability values into infrastructure decision-making becomes progressively more important. Yet, the term ‘value’ has been used under different meanings and implications throughout the infrastructure sustainability literature, obstructing the debate on which values are important and what is valuable to infrastructure decision-making processes. This paper reviews how the concept of value has been used to position different sustainability dimensions of large infrastructure systems. Specifically, a conceptual framework proposed by Tadaki et al is used to highlight different notions of infrastructure value under four general headings: value as a magnitude of preference, as a contribution to specified goals, as a means of communicating key priorities, and as a representation of historical relations. This review shows that the discussion of infrastructure value has often focussed on monetary measures to the exclusion of other relevant measures of value. However, if long-term sustainability goals are to be met, a transformation of the ways that value is understood and measured in the context of infrastructure systems is required. This review discusses key similarities, interdependencies, and disparities between published notions of infrastructure value in order to provide a conceptual reference guide that highlights the variety of perspectives that are both implicit and explicit among practitioners and academics.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".