Evolving consumer preferences for residential decking materials
Bibliographic record
Abstract
Major changes are taking place in the residential decking market driven by concerns over wood preservatives and the resulting phase-out of chromated copper arsenic (CCA)-treated wood and recent entry into the marketplace by wood-plastic composites. Using conjoint analysis, this study explores consumer perceptions regarding residential decking materials over two time periods, 2000 and 2003. Type of material and lifetime were the most important decking attributes. Of lesser importance were annual maintenance and price. Major changes took place over the three-year study period with respect to opinions towards treated wood and wood-plastic composites. Consumers became much more negative towards treated wood and wood-plastic composites received nearly equivalent gains. The CCA controversy clearly had an impact in the marketplace and we demonstrate the usefulness of conjoint analysis in capturing this change. Key words: decking, consumer, conjoint analysis, plastic lumber, treated wood, cedar, substitution
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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) | 0.001 | 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".