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Record W4408929961 · doi:10.1007/978-3-031-77752-3_19

Chinatown’s Key, Built Form Elements of Sense of Place: Findings from an Immersive Visual Survey

2025· book-chapter· en· W4408929961 on OpenAlexaffabout
Francisco Alaniz Uribe, Nathan Stelfox, Emily Kaing

Bibliographic record

Venue˜The œurban book series · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPlace Attachment and Urban Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChinatownKey (lock)Sense of placeVisual artsComputer scienceArtGeographyComputer securityArchaeologyEconomic geography

Abstract

fetched live from OpenAlex

Abstract Cities are made up of multiple diverse cultural areas that are rooted in heritage. These areas evolve over time experiencing pressures for change and redevelopment that can erode their sense of place and perpetuate their marginalization. Chinatown in Calgary is one of those areas with strong historical roots and under redevelopment pressure. An immersive, web-based public engagement process using 360-degree photography was used to measure the community’s perception of the importance and impact of built form elements on Chinatown’s sense of place. The built form elements prioritized included streetscape design and programming with a preference for pedestrian over vehicular traffic reflecting its historical use; the buildings’ architectural language with a complexity of motifs, and the use of traditional materials and construction technics that evoke its original culture; buildings respecting human scale; street-wall permeability; and signage as a visible reminder of the original languages. The findings of this study contribute to the understanding of how the built environment contributes to the sense of place in ethnic and heritage areas. They form the basis for urban design guidelines and contribute to more appropriate redevelopment proposals. Helps build inclusivity and a degree of certainty for the future of marginalized ethnic areas of our cities.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.443
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.308
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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