Urban Suburban: Redefining the Suburban Shopping Centre and the Search for a Sense of Place
Bibliographic record
Abstract
In today's suburban condition, the shopping centre has become a significant destination for many.Vastly sized, it has become a cultural landmark within many suburban and urban neighbourhoods.Not only a space for 'purchasing', the suburban shopping centre has become a place to shop, a place to eat, a place to meet, a place to exercise -a social space.However, with the development and conception of a big box environment and a new typology of consumerism (and architecture) at play, the 'suburban shopping mall' as we currently know it, is slowly disappearing.Consumerism has always been an important aspect of many cities within the Western World, and more recently it is understood as a cultural phenomenon 1 .Early department stores have been, and are, architecturally and culturally significant, having engaged people through such devices as store windows and a 'grand' sense of place.It is more recently that shopping centres have become a space for the suburban community to engage -a social space to shop, eat and purchase.Suburban malls, which were once successful in serving their suburban communities, are on the decline.These malls are suffering financially as 1 Hudson's Bay Company Heritage: The Department Store.Hudson's Bay Company.Accessed online Living in the sprawl Dead shopping malls rise like Mountains beyond mountains, And there's no end in sight… -Arcade Fire, Sprawl II (Mountains Beyond Mountains) 2010
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".