Big-Box Retail Development: Examining Complications, Understanding Trends, and Introducing Holistic Strategies to Minimize the Impacts on Communities
Bibliographic record
Abstract
Big-box stores are large-scale, single storey buildings such as Wal-Mart, Home Depot, Canadian Tire, and Rona, to name a few. These types of projects have been present in North American cities for decades and have offered one-stop shopping experiences and lower prices than smaller, independent stores. However, big-box stores, at times, also present social, cultural, and environmental issues. This thesis explores the development of big-box retailers and examines their contribution to public space within the urban design context through the lens of a holistic approach. Using holistic guidelines, big-box buildings are critically analyzed in order to reconceive a design that is functional, environmentally sustainable, and aesthetically appealing. An integrated design framework is then developed that offers strategies to manage the complex issues of big-box retail and development. It also provides holistic solutions for sustainable design, while promoting a sense of place and increasing the potential for an attachment to place.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".