Bibliographic record
Abstract
Coastlines have seen a shift in natural behavior in the past few years. Roughly a quarter of the world’s population reside nearby or on our current coastlines. Not only are the coastlines at risk but even more so each individual neighbourhood and the sense of belonging within them are at risk. Action has begun to be taken against climate change across many countries. Different coasts are at risk from different threats and different levels of danger. Common approaches have been used depending on how vulnerable a place is. Managed retreat is becoming an approach where people and neighbourhoods are moved further inland in order to be protected by the shifting seas. This allows a safe buffer between the sea and infrastructure while also maximizing the public space in-between. Lyall Bay is the focal case study for this research. The threatened beachfront and locals along create an opportunity to bridge the gap between resiliency against the shifting seas and preserving the local sense of belonging. Lyall Bay is known for it public space along the beachfront becoming a significant part of peoples sense of belonging within it. Managed retreat can become a strategy to transform the private space into a larger public space by removing hard infrastructure that is at risk while also allowing natural processes to occur leading to enhancing the sociability within it. This research undergoes an analysis on the existing social, physical and ecological structures and how these form and allow for a feeling of belonging for the locals. This project aims to enhance the existing ecological systems, preserve the sense of belonging and create a more resilient retreat for a longer lasting suburb. This research has to lead to an assemblage of findings that allow people to feel a sense of belonging within Lyall Bay. The beachfront is the main area where it becomes a place for everyone. It allows space for a variety of activities catering to a large number of different people. The design aims to preserve while also protecting the site ecologically by giving room for the dune systems to expand. It also provides safer housing opportunity that is situated over a buffer zone away from risks such as storm surge which Lyall Bay has experienced more frequently the past few years. The housing allows for a larger number of residents on site while creating retail opportunities through mixed use buildings. The design allows for a larger public space in between the sea and the residential space maximizing the sociability in between.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.861 | 0.694 |
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".