Bibliographic record
Abstract
In a time of recession, the challenge of building and planning for tall buildings has become even more complex; the economics of development, legislative and planning frameworks, and the local politics of development must be navigated by those wishing to design and construct new tall buildings which fit within the fabric of their host cities. This book is a timely contribution to the debate about new tall buildings and their role and effect on our cities. It is divided into two main parts. In part one, the relationship between tall buildings and planning is outlined, followed by an exploration of the impacts that construction of tall buildings can have. It focuses, in particular, on the conservation debates that proposals for new tall buildings raise. The first part ends with an analysis of the way in which planning strategies have evolved to deal with the unique consequences of tall buildings on their urban locations. The second part of the book focuses on seven examples of medium-sized cities dealing with planning and conservation issues, and implications that arise from tall buildings. These have been chosen to reflect a wide range of methods to either encourage or to control tall buildings that cities are deploying. The case studies come from across the western world, covering England (Manchester, Liverpool, Newcastle and Birmingham), Norway (Oslo), Ireland (Dublin) and Canada (Vancouver) and represent a broad spectrum of approaches to dealing with this issue.In drawing together the experiences of these varied cities, the book contributes to the ongoing debate about the role of the tall building in our cities, their potential impacts, and experiences of those who use and inhabit them. The conclusions outline how cities should approach the strategic planning of tall buildings, as well as how they should deal with the consequences of individual buildings, particularly on the built heritage.
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 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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".