Multi-stakeholder study on urban greening as Hong Kong's city branding practice
Bibliographic record
Abstract
This study explores Hong Kong’s potential to enhance its international position and social development through mainstreaming urban greening in its city branding exercise from the perspectives of local residents, overseas investors/workers and tourists. The variety of services by urban greeneries are theorised to be compatible with the economic and social purposes of city branding, as exemplified by Minneapolis, Vancouver, Singapore and London. Through literature review, despite enjoying exceptional green cityscape with the presence of urban parks, country parks, Hong Kong Wetland Park and other green facilities, the authority is considered unable to capitalise the strength under Hong Kong’s current branding exercise. The results from the questionnaire survey (n=240), focus groups (n = 10) and email interviews reveal that, while perceiving the current availability of urban green resources inadequate, people generally favour incorporating more green elements into the brand, mostly due to the positive correlation between urban green provision and quality of living. The mediocre ratings towards the current brand highlight a need to review the brand. The adoption of the proposal also necessitates the authority to enhance its work in the creation and management of urban green resources as well as environmental education.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".