Initiatives of Global Cities in Environmental Sustainability: A Case of London and New York City
Bibliographic record
Abstract
As global cities are the financial centers of globalized economy, they have attained much attention from global communities concerning local initiatives on environmental sustainability. Many global cities are vulnerable to global warming and adversities of climate change. In the United States, many cities and local government, including New York City, are taking their own initiatives to reduce greenhouse gas emission, whereas European cities are built historically with compact nature which is more sustainable. This study conducts a comparative analysis on local sustainability policies in New York City and London and focuses on the efficiencies of the initiatives taken by these cities. The comparative analysis reveals that there are more similarities than differences between London and New York City in regards to sustainability goals. However, approaches toward achieving sustainability goals are different in London and New York City due to dissimilarities in geography, local cultures, and diverse environmental politics. In conjunction with the government regulations, behavioral change of the citizens is also pivotal for achieving sustainability outcomes in global cities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".