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Record W2019277061 · doi:10.1080/14036090903159960

Power Dynamics and Perceptions of Neighbourhood Attachment and Involvement: Effects of Length of Residency versus Home Ownership

2009· article· en· W2019277061 on OpenAlexafffundabout
Arlene J. Carson, Neena L. Chappell, Carren Dujela

Bibliographic record

VenueHousing Theory and Society · 2009
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health ResearchHealth CanadaUniversity of California, Davis
KeywordsNeighbourhood (mathematics)Bivariate analysisQualitative propertyPerceptionQualitative researchSocial psychologyPsychologySurvey data collectionSociologyDemographic economicsPublic relationsPolitical scienceEconomicsSocial science

Abstract

fetched live from OpenAlex

Abstract This article explores neighbourhood attachment and involvement by comparing qualitative and quantitative data drawn from the same urban health promotion research project in Canada. Comments by community leaders in qualitative interviews linked increased attachment and involvement with the presence of greater numbers of home owners and greater length of residency of neighbourhood members. Bivariate and multivariate regression analyses of a large survey dataset collected for this same project were undertaken to explore whether these quantitative data corroborated or contradicted the comments from the qualitative interviews. Overall, analyses did not support the qualitative interview comments that a greater number of home owners in a neighbourhood would enhance attachment and involvement. Results are discussed in relation to how perceptions held by one group about another and related power imbalances may influence community members’ interest in and ability to interact with each other and thereby build community capacity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.025
GPT teacher head0.361
Teacher spread0.336 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations16
Published2009
Admission routes3
Has abstractyes

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