Socio-economic Characteristics of Dissatisfied Users of Wood-based Houses in the Czech Republic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although there has been an increasing interest in wooden construction in recent years, this type of constructions is still not as common as in the northern European countries (Sweden, Finland), the US, or Canada. The paper analyses users of wood-based houses in the Czech Republic. The paper presents partial results of this extensive marketing research, analyses dissatisfied users of wood-based houses and identifies socio-economic characteristics of the dissatisfied users. The survey was conducted by researchers from Mendel University in Brno in the year 2012 – 2014 and it covered 1,000 Czech households. Individual factors of perceiving wood-based houseś quality and price were processed both for the satisfied users and the dissatisfied users who would not purchase this type of building again. When processing the data obtained by the research the authors employed various analytical procedures. The prevailing data-analysis tools were basic statistical methods. The results for both groups were mutually compared. The paper deals with differences in socio-economic characteristics of satisfied and dissatisfied users of wooden family houses and makes recommendations for elimination of the number of the dissatisfied users.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it