A survey of private landlords in Karlsruhe and their perception of deep energy retrofit
Bibliographic record
Abstract
Abstract Energy use related to buildings accounts for 35.3% of Germany’s final energy consumption and nearly a third of greenhouse gas emissions. Thus, deep energy retrofit (DER) has a substantial role in the German energy efficiency strategy. Although many DER measures are economically viable, the pace of DER is below expectations and target value. A few studies investigated this phenomenon and conducted surveys mostly among owner-occupiers. However, 54% of the 40.5 million apartments in Germany are rented and a total of 15 million are let by private (not professional) landlords. Therefore, this investigation focuses on private landlords to find out what drives or constrains them to do deep energy retrofitting. A survey was conducted in a quarter of Karlsruhe, a large city in Germany with an above-average demand-driven real estate market. In this quarter, 83.2% or 8464 apartments are rented. 85 private landlords who own 10% of the rented residential buildings in the quarter responded and gave insight into their perception of DER. The results show that the buildings of the respondents originate from a construction period with large saving potential. Main strategies for investments in DERs are conservation of economic value of the property and the compliance with legal requirements. The main trigger is required maintenance. Despite an eco-friendly attitude, ecological criteria have a minor part in the DER decision. Finally, policy recommendations are made.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".