Bazaar model: Engaging community identity
Bibliographic record
Abstract
RESEARCH QUESTION \nCan the concept and architectural components of a traditional bazaar be used in Tāmaki Makaurau to reinforce its local community identity? \n \nABSTRACT \nIndividual identity plays a significant role in providing us with an understanding of the place we hold in this world. A community is created and represented by the actions of individuals that are influenced by their local context, which may include shared interests, experiences, and values. Traditional bazaars, as public spaces, are one of the greatest attainments of historical Islamic civilizations. The bazaar’s public spaces were regarded as a symbol of local community identity in their respective areas. The traditional bazaar is not only designed as a retail space, but is a public space serving as a microcosm in which economics of trade merged with aspects of social life. Ultimately, this had an impact of elevating the community by merging individual experiences and assisting the spread of shared values. Over time bazaars have successfully retained their true essence and are known as the ‘heart’ of the city. \n \nTāmaki Makaurau has always been a meeting place for different ethnicities, cultures and where people interact collectively. Today it retains its position as Aotearoa’s largest and most populous city and the nation’s economic engine. Tāmaki Makaurau has become a melting pot of culture with its dynamically buoyant cultural milieu, evident through its openness to outside influences and people, with different identities that call it home. This unique identity of Tāmaki Makaurau and its connection to its roots should be embraced and reinforced through architecture. \n \nThis project will explore ways to analyse a traditional bazaar model and break down key architectural concepts and components that make them successful public spaces that showcase the relationship between people, community, and their space. The goal is to adapt and develop these architectural components in an attempt to design a public space unique to a specific, chosen local context in Tāmaki Makaurau. The concepts and components of a traditional bazaar model will be researched and applied to create a complex, multi-purpose structure, providing a public space aiming to successfully embrace and reinforce the identity of the chosen local community. \n \nSite: Opposite the upcoming Karangahape Train Station on Mercury Lane, between Cross Street & Canada Street
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".