Spatial ethics as an evaluation tool for the long-term impacts of mega urban projects: An application of spatial ethics multi-criteria assessment to Canning Town regeneration projects, London
Bibliographic record
Abstract
Decision-making processes for mega urban infrastructure developments are far from closed rational systems. They rarely satisfy everyone, and are politically driven, reflecting the interests of key stakeholders and macro-scale economic development goals, with limited evaluation of multi-scale impacts and unwanted negative consequences to society at large. An integrated approach to evaluating impacts is required in consideration of the spatial and thus unavoidably ethical, political nature of decisionmaking on mega infrastructure development. Spatial Ethics (SE) is addressed as a conceptual basis to investigate the multi-scale impacts and the spatial equity issues of urban infrastructure development. SE multi-criteria assessment (MCA) has been explored as a tool to evaluate urban transport projects in respect of plurality of actors, interests and priorities by involving stakeholders in shaping the framework as well as evaluating the impacts. A case study, which applies the framework, identifies that urban transport infrastructure investment brings benefits and costs related to urban spatial transformation. The positive return to society over time and space is limited from the spatially ethical perspective; however, identification of winners and losers cannot be generalized as the impacts are perceived differently by individuals who are affected by various external and internal factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".