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Record W3214147514

Understanding sense of community in a master planned community in Richmond's Oval Village

2021· article· en· W3214147514 on OpenAlexaboutno aff
Zolzaya Tuguldur

Bibliographic record

VenueSummit (Simon Fraser University) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsSense of communitySociologyGeographyPolitical scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.004
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 head0.170
GPT teacher head0.337
Teacher spread0.166 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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