An investigation of hardwood plywood markets. Part 1. Architectural woodworkers
Bibliographic record
Abstract
This is the first part of a two-part study investigating markets for hardwood plywood. North American architectural woodworkers were surveyed to better understand the structure and use of wood-based panels in the industry. A questionnaire was mailed to a sample of U.S. and Canadian architectural woodworkers. The sample consisted of members of the Architectural Woodwork Institute (AWI) and the Woodwork Institute of California (WIC). The response rate, adjusted forbad addresses, was 31 percent. The average architectural woodworker purchased $283,000 of panel materials in 1997, and $111,000 of hardwood plywood. Of total panel purchases, hardwood plywood (including all substrates covered with a hardwood veneer) represented 37 percent, followed by melamine-coated board (21%), raw particleboard (17%), and high-pressure laminate (8%). The Northeast region represented 38 percent of total hardwood plywood purchases by architectural woodworkers followed by the Midwest (20.4%); the Southeast (14.9%); the West (9.1%); and the South Central (8.3%). Of the hardwood plywood purchased, 37 percent was particleboard core, 33 percent veneer core, and 24 percent medium density fiberboard core. Sixty-three percent of total hardwood plywood was premium grade, followed by custom (25%), and paint grade (7%). Red oak was the predominant face species used (31%), followed by maple (17%), cherry (16%), birch (10%), and mahogany (9%). Eighty-two percent of the faces were constructed of sliced veneer. Nearly 4 percent of total hardwood plywood purchases were of pre-finished plywood. This number was expected to increase to nearly 7 percent by the year 2000. The most important hardwood plywood attribute as perceived by architectural woodworkers was absence of delamination of veneers, followed by absence of defects showing through face, on-time delivery, absence of warp, and orders shipped correctly.
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 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".