An investigation of hardwood plywood markets. Part 2. Fixture manufacturers
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
This is the second part of a two-part study investigating markets for hardwood plywood. Part 1 dealt with architectural woodworkers. North American fixture manufacturers 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 fixture manufacturers. The sample consisted of members of the National Association of Store Fixture Manufacturers (NASFM). The response rate, adjusted for bad addresses, was 20 percent. The average fixture manufacturer purchased $1.2 million of panel materials in 1997, and $244,000 of hardwood plywood. Of total panel purchases, medium density fiberboard (MDF) represented 28 percent, hardwood plywood (including all substrates covered with a hardwood veneer) represented 20 percent, melamine-coated board was 20 percent, raw particleboard was 15 percent, and high-pressure laminate was 11 percent. Of the hardwood plywood purchased, 47 percent was MDF core, 34 percent was particleboard, and 14 percent was veneer core. Sixty-four percent of total hardwood plywood was premium grade, followed by custom (27%), and paint grade (5%). Red oak was the predominant face species used (31%), followed by maple (24%), cherry (11%), birch (10%), and white oak (5%). Fifty-two percent of the faces were constructed of sliced veneer. Over 6 percent of the total hardwood plywood purchases was of pre-finished plywood. This number was expected to increase to 12 percent by the year 2000. The most important hardwood plywood attribute as perceived by fixture manufacturers was absence of delamination of veneers, followed by on-time delivery, orders shipped correctly, and shipment arrives in good condition.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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