Urban Green Space and Urban Biodiversity: Kuala Lumpur, Malaysia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Urban green space plays an important role in enhancing the quality of environment especially for urban biodiversity. Declining biodiversity around the world has received much attention among academics, professionals and citizens. The United Nations has declared year 2010 as the ‘International Year of Biodiversity’. Urban biodiversity movement is important to ensure healthy city environments. Despite this ongoing movement, urban dwellers have little knowledge about conservation of biodiversity particularly wildlife. Moreover, biodiversity has received little attention from built environment practices (Brown & Grant, 2005; Niemelä, 1999). In general, urban wildlife habitat is protected as reserved forest. Many species of wildlife are generally found in such reserved forests. In comparison, the scale of urban parks in Kuala Lumpur is massive, much larger than protected forests. This paper presents the situation of urban wildlife species and the quality of habitats in Kuala Lumpur. It is found that many factors contribute to the healthy conservation of urban wildlife such as quality and variety of habitats, ornamental versus native vegetation and ecological design. The findings highlight that common urban birds are dominant in urban green spaces regardless of the size of the green spaces. However, only larger urban green spaces help protect species. Finally, the study concludes that urban wildlife in Kuala Lumpur is rapidly declining and that there is a greater need for the community and stakeholders to promote programs and activities to preserve and enhance urban wildlife. Development of comprehensive acts, policies and guidelines are vital for urban wildlife protection.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it