Urban Life and the Changing City
Bibliographic record
Abstract
Cities hold both the promise of economic opportunities and social mobility yet at the same time are hosts to massive poverty and social exclusion. The nation is confronting a host of problems associated with urbanisation common to the contemporary world, such as the impact of the auto mobile and mass transits, and the pressure of modernity on traditional society and community life. The impacts of our urbanites society coupled with the common issues of modern world certainly had impacted our society and cultural values that we have uphold for generations.This paper takes a critical look at issues plaguing urban life and argues that the perfect modern city living is only in a state of mind and our daily existence are already radically different from the urban images we carry in our minds and hearts. Our city has suffered from the dreary sea of uniformity, lacking in the diversity of orchestration of spaces to completely evoke a complex and dynamic public use.This paper identifies the factors which contribute to the phenomena and that have an impact on the makings of a liveable city. This paper reiterated that the challenge lies ahead of us to make changes and improvement to our cities for the loss of our great public life and public realm in city spaces. Urban public spaces when given prominence and focus can achieve monumentality and serve as a marker or gesture for the public to engage socially. Our city must invest its future in these spaces by creating all the opportunities and forms to respond to a dynamic public environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.025 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".