Bibliographic record
Abstract
Sustainability is sometimes thought to be about conserving natural resources, but in reality it is about living in ways that are enduring and resilient for the long term. In the modern world, people are placing heavy demands on the planet, with carbon fuel extraction, water pollution, and damage to natural environments. As the world has urbanised, this has accelerated. Increasingly more people are living in cities, moving away from low-density, localised lifestyles towards more intense, resource-hungry activities. More than two thirds of the world’s population are expected to live in cities by 2050, so future housing is fundamental to climate adaptation and sustainable development. Irish homes use almost one quarter of the energy produced in the country, and it is increasing. At policy level, both energy upgrades to homes and higher standards for new homes are priority areas for climate adaptation. More broadly, however, a technical upgrade of building standards is just one part of the challenge: Of greater importance, is where new development takes place, and how the design of new communities supports more sustainable living. Upgrading the building fabric of a home may reduce the energy bills, but if the residents are commuting long distances by car much of this benefit is lost. In the built environment, housing can be seen as physical infrastructure. However, it is also the social and economic infrastructure that frames the operation of society and the economy. These too must be sustainable. By its nature, the production of housing is also an economic engine of capital formation and employment, so, these too must be aligned. The United Nations sustainable development goals (adopted by Ireland in 2015) include an objective to make ‘cities and human settlements inclusive, safe, resilient and sustainable’. .
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.009 |
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".