A Research Design to Build Effective Partnerships between City Planners, Developers, Government and Urban Neighbourhood Communities
Bibliographic record
Abstract
Communities of place feature prominently in new urbanism movements and in master-planned inner-city developments that result from urban renewal. This papers point of departure is the stark contrast between the widespread use of mobile and ubiquitous media and communications technology by urban dwellers on the one hand and endemic forms of urban alienation and the disappearance or non-existence of urban neighbourhood community identity on the other. Networked individualism introduces challenges to conventional understandings of place and public places. It opens up opportunities to build partnerships between architecture, city planning and urban studies in order to re-conceptualise the understanding of community and neighbourhood planning in the light of new media and network ICTs. However, such a re-conceptualisation has not been achieved yet because of a lack of theoretical and practical understandings of the freedom and constraints and the social and cultural meanings that urban dwellers derive from their use of place-based ICT systems. The paper argues that in order to gain a better understanding of the continued purpose and relevance of urban neighbourhood communities in metropolitan areas and their changing role within a network society, the scope and structure of the communicative ecologies and social networks created and maintained by residents in urban residential real estate needs to be investigated empirically to inform city design and planning. The paper discusses a cross-disciplinary research design to build effective partnerships between city planners, developers, government, education and urban neighbourhood communities.
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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 | 0.051 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".