Testing for variation in the western Oregon softwood log price structure
Bibliographic record
Abstract
Timber owners in western Oregon have been concerned about the erosion of price premiums for higher quality grades of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) sawlogs over the past decade. Time series tests indicate that the ratio of 3Saw (lower quality) to 2Saw (higher quality) sawlog prices did rise over the 19902000 period, suggesting convergence between the prices. To identify causes of this trend, we estimate reduced form equations for Douglas-fir sawlog prices with time-varying coefficients using flexible least squares. Log grade prices were related to prices of lumber by grade, prices of chipped residues, labor wage rates, and volumes of public timber supplied. Changes in the relation of log grade prices are reflected through changes in both reduced form coefficients and levels of the exogenous variables. Changes in the coefficients, in turn, may derive from shifts in the distribution of log qualities within grade categories and from grade-specific changes in sawing and log production technologies. Coefficient trends showed that higher quality lumber grades became more important for 3Saw logs during the sample period, while lower quality lumber grades and chips became more important for 2Saw, moving the log grade prices closer together. Comparison of simulated 2Saw and 3Saw prices with and without historical time patterns in the exogenous variables had little impact on their relationship, suggesting that factors shifting the coefficients may have been the primary drivers of price convergence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".