Environmental Assessments in Architectural Competitions in Poland in the Years 2018–2022
Bibliographic record
Abstract
This paper discusses environmental and energy-saving factors in architectural competition procedures. The final assessment of sustainability and environmental aspects of a building is a derivative of the decisions taken during the entire project execution process, especially those taken at the initial stage. Notifications concerning architectural competitions, both in Poland and other European countries, as well as in the United States and Canada, increasingly often list sustainability as a necessary criterion. Aspects such as the use of renewable energy sources, energy efficiency solutions or reducing a building’s occupancy costs most often appear as guidelines. In this paper, the authors discuss the essence of solutions in architectural competition procedures announced in Poland in the years 2018–2022, using 154 cases as an example and setting them against the background of Europe. The types and level of detail of the selected criteria and their frequency of occurrence were examined. The study unveiled the absence of comprehensive guidelines in the processes of nationwide architectural competitions that take sustainability into account. The lack of definitions for environmental and energy objectives has a significant impact on their integration into competition designs, and reduces the chances of adapting and adopting these aspects at a further stage. Based on the analysis, a range of recommendations were formulated for implementation in competition procedures.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".