Understanding sense of community in a master planned community in Richmond's Oval Village
Bibliographic record
Abstract
This research is aimed at understanding sense of community among residents of a master planned community in Richmond's Oval Village.In particular, my research investigates how affordable housing tenants of Cadence perceive the quality of their social interaction with others and their feeling of sense of community.A mixed-method approach consisting of an online survey and semi-structured phone interviews was chosen as the research design with the affordable housing tenants of Cadence to capture their experience living in a mixed-income development.Ten affordable housing tenants completed the survey and 7 of them participated in the follow-up interview.Key informant interviews were conducted with the housing operator as well as the City of Richmond staff members to supplement the findings from the tenant survey and interviews.In addition to filling the knowledge gap around whether master planned communities foster positive social interaction and sense of community among residents, especially in the context of a Canadian suburban city, I hope my research findings will help inform planners how mixed-income housing can be improved in terms of design and implementation to ensure it is socially inclusive and equitable for all.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".