Bibliographic record
Abstract
Contemporary environmental and economic factors make the construction of narrow-front townhouses a continuous attraction. As affordability is a primary concern for many homebuyers, opting to buy a townhouse can provide the cost savings they are seeking. With their dense planning pattern, building townhouses results in the reduced cost of services and land and affordability is achieved. However, limitations to community planning occur, namely, challenges to circulation and open space. These are two critical issues that need to be resolved early on; using principles and case studies, this paper will offer strategies for maximizing efficiency and functionality in communities that use townhouses as their main design feature. In designing communities with townhouses, it is imperative to begin by paying close attention to roads and parking as well as location and content of public and private open spaces. These issues will define the character of the community. When choices are made about the location of the dwellings in conjunction with these aspects, a liveable place will emerge and the stigma associated with developments with low-cost townhouses will be alleviated. Despite the fact that townhouses are a building typology rooted in earlier centuries, its many attributes makes it relevant to our time. It preserves the advantage of private residential living, yet offers higher density and the possibility to create sustainable communities.
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 | 0.001 | 0.003 |
| 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 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".