Scientometric Analysis on Climate Resilient Retrofit of Residential Buildings
Bibliographic record
Abstract
This study aims to understand the impacts of climate change and extreme climate events on residential buildings and explore how existing buildings can be adapted to resist these negative impacts. A bibliometric and scientometric analysis was conducted on resilient residential retrofits to highlight the prevalent themes, critical directions, and gaps in the literature, which can inform future research directions. The resilient residential retrofit publications from 2012 to 2023 were retrieved and analyzed using text-mining software. In all, 4011 publications and 2623 patents were identified. The analysis revealed an average annual publication growth rate of 11%, indicating increasing interest in resilient residential retrofits. Four central topics were explored specifically throughout the study, as they are known to be the most prevalent climate risks for residential buildings: Overheating, Flooding, Wind, and Wildfires. The research trends analysis reveals that emerging interests in resilient residential retrofit encompass nature-based solutions, energy efficiency, thermal comfort, microclimates, durability, post-disaster recovery, and extreme events. Nearly half of the publications reference urban context and over one-third mention costs. The building envelope is the most frequently discussed housing component. Although energy retrofit was not the primary focus of this study and was not specifically searched for, energy concerns were still prevalent in the dataset, highlighting the critical importance of energy efficiency and management in resilient residential retrofits. The analysis of R&D momentum revealed several research gaps. Despite high growth rates, there are low publication rates on key topics such as durability, holistic approaches, microclimates, nature-based solutions, and traditional homes, to name a few. These areas could benefit from further research in the context of climate-resilient residential retrofits. Additionally, the analysis indicates a lack of publications on cross-themed research specific to rural and suburban settings. There are also few studies addressing combinations of themes, such as overheating in high-rise buildings, wildfires in Nordic climates, and flooding risk in smart homes within the scope of resilient residential retrofits. The United States leads in publication output, followed by China and the UK, with China dominating the patent landscape. This scientometric analysis provides a comprehensive overview of the research landscape in resilient residential retrofit, systematically maps and analyzes the vast amount of research output, and identifies the key trends and gaps, enabling us to see a type of quantitative snapshot of the research in a field at a certain point in time and thus providing a unique point of view. This study helps stakeholders prioritize efforts and resources effectively for guiding future research, funding decisions, informing policy decisions, and ultimately enhancing the resilience of residential buildings to climate-related challenges.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".