An evaluation of neighbourhood sustainability assessment frameworks using ecosystem characteristics and principles of systems resilience as the evaluation criteria
Bibliographic record
Abstract
If human societies are to sustain over the long-term, we must manage human societies and our products, including settlements, to work within the context of a living environment. While conventional practice in neighbourhood planning has made advances in acknowledging the importance of sustainability in the built environment, it generally does not acknowledge fundamental ecological concepts such as the ecology of sites, global ecological productive carrying capacity or the dynamic nature of a living, rapidly eroding, biophysical environment. This thesis articulates the need to acknowledge the ecological context as the basis of sustainable communities. A living ecological system is not only the context in which settlements operate; ecosystems may also be a viable model from which to form settlements. This thesis proposes incorporating the model of ecosystems, the characteristics they embody and principles by which they are governed into the planning and design of settlements as a method of informing a physical form that can support sustainable communities. A case study of a local Vancouver neighbourhood, False Creek North, is used as a tangible reference point around which to frame the discussion of sustainable communities. Although not planned explicitly to be a “sustainable community” the neighbourhood embodies many of the characteristics of conventional thinking about sustainable neighbourhoods. Using sustainability assessment frameworks, the False Creek North development is evaluated for sustainability merits and weaknesses in order to understand how this model of development could be improved to better reflect concepts of sustainability. In order to ensure that the frameworks reflect a strong, ecologically bound concept of sustainability the assessment frameworks are also evaluated based on their ability to capture characteristics and principles of ecological systems using an evaluation matrix. An integrated discussion is presented on a) how well the frameworks reflect ecological principles and b) what elements of FCN display ecological sustainability characteristics. Overall, the assessment frameworks are found to be limiting in their ability to capture fundamental ecological concepts. Indicators that reflect ecological principles and characteristics are therefore proposed and examples are given as to how they might be used to measure aspects of the case study site, False Creek North.
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 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 | 0.087 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".