Credit Availability: A Possible Barrier to Growth for the Alaska Forest Products Industry?
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
Abstract Historically, the Alaska forest products industry has been driven by pulp production and the export of logs and cants primarily to Japan. Economic stagnation in Japan, the closure of Alaska's two pulp mills, harvest restrictions, and increased competition have severely impacted the industry. To survive, the industry must make significant investments in capital equipment, which requires adequate access to business credit. This article examines whether credit availability is a barrier to the future growth of the industry. Data were collected through a mail survey in spring 2002. Our results show that credit rationing is prevalent throughout the industry. Lack of experience and low collateral are identified as the two main causes. An educational program and loan guarantees are offered as policy prescriptions to help alleviate credit rationing. West. J. Appl. For. 20(3):177–183.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it