Routledge handbook of urban landscape research
Bibliographic record
Abstract
"Landscape architecture is one of the key professions dedicated to making cities hospitable and healthy places to live, work and play, while respecting and enhancing the natural environments and landscapes we inhabit. This edited collection presents current writing about the pivotal roles that landscape architects play in addressing some of the most pressing problems facing the planet, its environments and its populations through their research, analysis and speculative practice. The book has assembled current writings on recent research structured around five major themes, including: Governance, Power and Partnership; Infrastructure, Systems and Performance; Environment, Resilience and Climate Change; People, Place and Design; and Culture Heritage and Identity. As a collection, the chapters demonstrate the diversity of themes and topics that are expanding the scholarly body of knowledge for the discipline and its relevance to the practice of landscape architecture. The contributors to this book are academic researchers and practitioners from the discipline of Landscape Architecture. The chapters draw on their research, teaching, and experience as well as analysis of project examples. Fifty-two contributors from the USA, UK, Sweden, Denmark, The Netherlands, Nigeria, Malaysia, Spain, Colombia, Australia, New Zealand and Canada discuss a diverse range of contemporary themes in urban landscape architecture. Collectively, the contributors demonstrate the breadth of experience, shared concerns and distinct issues that challenge urban landscape architecture and cities in the 21st century"--
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.091 | 0.051 |
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".