A Home Among the Gumtrees - Reimagining suburban Sydney for a hotter future
Bibliographic record
Abstract
This thesis started with a desire to delve into the impact that natural disasters have on small communities in an Australian context, how climate change exacerbates their effect, and the role that design can play in mitigating the impact on people and the natural environment. Initial research into bushfires, drought, floods, and heat landed this project in Western Sydney, in an area not far from where I grew up. Throughout the process, the project evolved into a dissection of the way that Sydney’s sprawling development worsens the effect of extreme heat in the suburban landscape, creating unliveable and unhealthy neighbourhoods unfit for the future. The suburban sprawl on the fringe of Australian cities is seen elsewhere across the globe. Heralded at the “Great Australian Dream” in the 20th century, homeownership and a quarter acre block of land were synonymous with success, social status and the ultimate way of living. Today, this model of development is unsustainable for the growing population and scarce availability of land in cities such as Sydney. Promoting car-centric mobility, worsening the urban heat island effect, and creating social isolation, this dream has quickly become a nightmare. So my question became, what does suburban living look like in the hotter future climate of Western Sydney? How can design work to retain the positive attributes of the Australian way of living, but with a sensitivity to the land, to our communities, and an appreciation of our limited resources? My design solution rests somewhere between nostalgia for the dream of a home among the gumtrees and criticism of this short-sighted way of housing growing communities.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".