A post-industrial paradigm for sustainable architecture via an open system model
Bibliographic record
Abstract
This paper critically analyses the unsustainable industrial pattern pervasive in modern architecture.From an environmental perspective, the aesthetic features of modern architecture range from environmentally de-contextual to environmentally irresponsible.In response to the imperatives of sustainable design in the built environment, the author explores a new paradigm via a model of open systems evolution, which is offered as a new paradigm for sustainable architecture.It refl ects the worldview of post-modernism whereby the creativity and complexity of the universe is self-organised achieving the emergence of order out of chaos.Underpinned by evolutionary thermodynamics and complex systems science, a model of open systems evolution consists of mechanisms such as open systems adapting to a host environment via natural gradients to optimize resource distribution and minimize entropy production in the host environment.Following this model, the author proposes a conceptual framework for sustainable architecture that describes the ecological interactions of buildings with their natural environment in open thermodynamic terms, with active involvement of end-users in micro-climate control.These multiple communications between buildings, nature and end-users obey the laws of open systems evolution, in order to optimize the environmental performance of buildings while meeting the functional needs of end users, resulting in a sustainable symbiosis of architecture and nature.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".