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Record W1966266630 · doi:10.5558/tfc82253-2

Evolving consumer preferences for residential decking materials

2006· article· en· W1966266630 on OpenAlexaffvenue
David Fell, Jon M. Thomas, Eric Hansen

Bibliographic record

VenueThe Forestry Chronicle · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsChromated copper arsenateConjoint analysisPulp and paper industryPreservativeEngineeringEconomicsPreferenceFood scienceChemistry

Abstract

fetched live from OpenAlex

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

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.070
GPT teacher head0.231
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2006
Admission routes2
Has abstractyes

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