The legitimation of private net zero emission building standards in the context of global decarbonization goals
Bibliographic record
Abstract
Since the Paris Agreement – where nations committed to decarbonizing their economies – private net zero standards have proliferated. Yet, their limited scope and ability to deliver tangible change threatens their legitimacy. For some scholars, this reflects societies’ limited capacity to envision pathways towards a fossil-free future. This raises questions about how private net zero standards are legitimised. Combining insights from the literature on legitimation, discourse analysis, and sociotechnical transitions, we analyse the legitimation of Net Zero Carbon Buildings by the World Green Building Council, the strongest global sustainable construction network. We find that net zero standard legitimation is a dynamic multilevel, multistakeholder process based on three strategies: vertical nesting, ambivalence, and conflict avoidance. This process perpetuates assumptions about growth, authority, and appropriate scales of action. This incremental, emission-focused approach to decarbonization is shielded from critique through claims that it contributes to broader sustainability objectives. By reproducing institutionalized narratives, global standard setters create a sense of consensus. However, this perception of consensus fails to address the complexities of implementation, contextualization, and integration of broader environmental and social concerns. These findings raise doubts in both theory and practice about the capacity of the construction sector to decarbonize through current strategies.
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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 | 0.028 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.055 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".