The Third Succes Factor of Renovations with Energy Ambitions
Bibliographic record
Abstract
Everyone acknowledges the importance of sufficient financial resources and wellfunctioning technologies when it comes to renovation processes with energy ambitions. However, Dutch experiences show that these two factors alone do not automatically result in success. More is needed, and this ‘more’ has to do with less concrete, but in the existing living environment very influential factors such as emotions and wellbeing. This hard to grasp factor is called ‘the third success factor of energy friendly renovation processes’. In the Netherlands, the questions ‘What exactly is this third success factor?’ and ‘How to integrate knowledge about this third success factor in the rational-oriented building industry?’ have been put high on the agenda of people who want to achieve the national energy goals related to the built environment. Research that combines knowledge from human sciences with energy efficient renovation experiences, the development of new educational methods, and a search for success stories has been part of joined efforts to find answers to these questions. A national knowledge platform called ‘HomeMates’ has been established to bundle and share all these findings. The Dutch experiences are described and discussed in this paper. They are also linked to Canadian experiences, based on the results of a project of Parallel52⁰ , the Dutch Canadian Sustainable Building and Planning network. In this project, Dutch findings and findings in the Toronto area were compared and discussed.\n\nAwarded for best paper
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".