Exploring the Role of Commercial Streets: Characteristics Influencing Sense of Place and Design Principles for Successful Placemaking
Bibliographic record
Abstract
ABSTRACTStreets are one of the crucial parts of open public spaces, which depict the character and sense of place in cities.The streets possess several functions that characterize their sense of place in the cities and at the same time depictthe character of cities by their physical appearance. Due to the unfit development of street characteristics,changing some of them, and remove others, the sense of place is interrupted, thus, affecting the people's feelingsand perception of the streets. This paper attempts to review the roles of the physical characteristics of commercialstreets in giving the sense of place in city centers. It aims to determine the theoretical framework of the role ofcommercial streets' physical characteristics in the creation of a sense of place in city centers. The paper reveals thatlocation, physical appearance, landscape features, and quality of views represent as the physical characteristics instreets, which differingly play various roles toward accessibility, recognition, legibility, safety, comfort, andvisibility.Commercial streets are living spaces that have a strong role in the socio-economic and cultural life of acity. These streets serve as commercial hubs, social platforms, and indicators of urban identity; they are highlyinfluential in determining the "sense of place," which is an integration of physical, cultural, and emotional qualitiesthat characterize a place. This paper explores the characteristics of successful commercial streets and identifiesdesign principles that can enhance their role in urban life. A comparative analysis of Oppanakara Street inCoimbatore, Pondy Bazaar and Sowcarpet in Chennai, Chandni Chowk in Delhi, Times Square in New York, andGranville Street in Vancouver points to best practices, yet common challenges are also brought out. This paperconcludes with suggestions for making the commercial streets more inclusive, sustainable, and culturally vibrant inthe pursuit of strong place-making.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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".