Bibliometric and visual analysis of sustainable preservation of heritage gardens
Bibliographic record
Abstract
Abstract Heritage gardens represent the cultural heritage pride of many nations, and their sustainable preservation has garnered widespread academic attention globally. Despite numerous qualitative reviews, a comprehensive quantitative analysis of heritage garden preservation literature from 2004 to 2024 is lacking. This study examines the dynamic evolution of heritage garden conservation (2004–2024) through bibliometric analysis, focusing on Research Activity and Impact, Cooperation Networks, and Knowledge Structure and Thematic Evolution. To achieve this goal, this study conducted a bibliometric analysis using the Web of Science Core Collection database. Initially, 1,540 documents were retrieved. After excluding irrelevant categories and conducting a manual review of titles, abstracts, and keywords to ensure relevance, 774 articles were selected for analysis. The analysis utilized bibliometric software tools such as VOS viewer, CiteSpace, and Biblioshiny. The results initially reveal that the period from 2010 to 2021 marked a significant increase in publication volume within the field of heritage gardens, although only 2.4% of the papers were reviews. Landscape Urban Planning and Geoheritage emerged as the most influential journals, based on their high local citation counts within the field. Additionally, collaboration networks indicated that scholars from the United States and China published the most papers, with Canadian scholars’ works having significant impact. Influenced by the evolving concepts of technology, politics, and cultural heritage, the analysis of knowledge structure and theme evolution identified ecosystem services, user perceptions, and cultural landscape impacts as recent hot topics. Future research on the sustainable preservation of heritage gardens should focus more on balancing urban development, incorporating sustainable management, and digital restoration through quantitative methods. In summary, this study offers insights into the global evolution of heritage garden preservation from 2004 to 2024, providing a valuable resource for future research and policy-making.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.184 | 0.179 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".