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Record W4388713533 · doi:10.1080/08111146.2023.2276448

Collaborative Neighbourhood Governance: Investigating Two Types of Resettlement Neighbourhoods in Suburban Shanghai, China

2023· article· en· W4388713533 on OpenAlex
Zhu Qian

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueUrban Policy and Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCorporate governanceNeighbourhood (mathematics)ExpropriationUrbanizationPrestigeBeijingPoliticsChinaLegitimacyCollaborative governancePolitical scienceEconomic geographyPublic administrationEconomic growthSociologyGeographyBusinessEconomicsLaw

Abstract

fetched live from OpenAlex

China's state-sponsored urbanisation has resulted in land expropriation – induced neighbourhoods that accommodate resettled villagers. The complexity of resettlement neighbourhood governance requires multiple governance nodes. Informed by two types of resettlement neighbourhoods in suburban Shanghai, this study examines the horizontal and vertical structures of collaborative neighbourhood governance. The study reveals that the government nodes have more power and authority, and other neighbourhood-based organisations need to be better represented in their competition for power, social prestige, political legitimacy, and economic resources. The consolidation of fragmented governance relationships calls for equally empowered networks and societal and economic inclusiveness.

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.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.546
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.001
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 head0.050
GPT teacher head0.410
Teacher spread0.360 · 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