Investigation of the relationship between place characteristics and child behavior in residential landscape spaces: a case study on the Century Sunshine Garden Residential Quarter in Hefei
Bibliographic record
Abstract
This paper reviewed child behavior in Chinese residential landscapes. A field survey was used to investigate place characteristics, whereas fixed-point observation and visualization records were utilized to analyze child behavior. Children were then classified into two categories, namely, those with action capacity and those with little capacity. Based on the classification and comparative analysis of place characteristics, along with the quantitative and visualized analysis of child behavior, the relationship between these two aspects was determined, and the effect of spatial elements in the selected residential areas on such a relationship was clarified. Additionally, the designing of a comprehensive landscape space that satisfies children's needs was also discussed. The conclusions are as follows: (1) Waterside is the element that most significantly affects child behavior. Children who can act on their own prefer to play along the waterside. (2) Open spaces attract children with action capacity, whereas children with little capacity tend to choose more private spaces. (3) Despite the presence of facilities for various activities, an extremely open space or one that is separated by a road still affects child behavior. (4) A comprehensive space with a water landscape, fitness facilities, high accessibility, and a number of cultural events may significantly affect child behavior. Both types of children were found to enjoy a place with such characteristics. Therefore, the evaluation of residential landscape space should be integrated with landscape design.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".