How to reinterpret an Alpine eco-monster. Application of the method of choice experiments for the design of a reuse project
Bibliographic record
Abstract
This paper deals with the role of evaluation methods for supporting the design process of sustainable urban and territorial transformations.In particular, the article considers the technique of Choice Experiments (CE) and it proposes a real application of the method for driving the decision-making process related to the reuse project of an abandoned building located in the Italian Alps.The evaluation model is based on different attributes of the reuse project, both tangible and intangible, including internal organization, external areas, accommodation structures and cost.In the evaluation, a questionnaire has been developed for the investigation of the preferences of potential users with reference to alternative reuse scenarios.The results of the application allowed us to determine the importance of the different attributes for the definition of the reuse strategy as well as the economic value of the selected strategy.The study proposed in this paper represents an innovative context of application of the CE method, regarding the economic evaluation of architectural buildings and landscape.A second innovative element of the present research concerns the use of the Choice Experiments approach for supporting the design of alternative solutions for a complex decision making problem.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".