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Record W1987024575 · doi:10.1177/0002764215580610

Toward a Relational Account of Neighborhood Governance

2015· article· en· W1987024575 on OpenAlexaff
Qiang Fu, Shenjing He, Yushu Zhu, Si‐ming Li, Yanling He, Huoning Zhou, Nan Lin

Bibliographic record

VenueAmerican Behavioral Scientist · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGrassrootsCorporate governanceSocial capitalRestructuringSpace (punctuation)Social network (sociolinguistics)Social relationInterpersonal tiesNetwork governanceCollaborative governanceSociologySocial network analysisSocial psychologyPolitical sciencePsychologyBusinessSocial scienceComputer sciencePolitics

Abstract

fetched live from OpenAlex

Although changes in urban space often mean a restructuring of social relations, few studies elucidate why network-related frameworks are inherently related to residential outcomes in urban neighborhoods. By proposing a relational account of neighborhood governance, we investigate outcomes of neighborhood governance by incorporating a series of measures of network forms of organization, network-based social capital, and neighborly interactions. Based on a collaborative survey project conducted in Guangzhou, we find that neighborhood ties and neighborly interactions are positively associated with neighborhood attachment and cohesion, whereas uneven power relations between grassroots governments and civic homeowners associations are negatively associated with these two measures. These results not only reveal new social dynamics in urban space but also lend support to a relational account of neighborhood governance.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.140
GPT teacher head0.447
Teacher spread0.306 · 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

Citations25
Published2015
Admission routes1
Has abstractyes

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