When the Mill Goes Quiet: Maine Paper Industry 1990-2016
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
The paper industry has been a mainstay of Maine’s economy for over a century. Paper mills in all corners of Maine employed numerous workers, purchased wood and supplies locally, and contributed significantly to the state’s industrial base. This conferred not only local recognition but political influence in Augusta. All concerned viewed the paper industry, based on Maine’s extensive forests, proximity to large Northeastern paper markets, abundant hydropower, and a trained workforce, to sustain these communities for another century. By 1990, however, a series of slowly shifting forces began to accelerate, threatening the industry’s cost competitiveness. Larger mi ls based on low-cost fiber appeared globally. At a dizzying pace, electronic communications replaced traditional print media, the principal market for most Maine mills. One after another, leading national companies cut back or closed mi ls, sold land, and finally sold surviving mills to investment groups. The quarter century after 1990 became a challenging time that left a number of former mill towns with lost tax bases, high unemployment, and uncertain futures. The author is a semi-retired forestry consultant living in Wayne, Maine. He attended college at Michigan State and University of Arizona and earned his doctorate at Yale. Following brief stints at the US Forest Service and the Yale School of Forestry and Environmental Studies, he came to Maine to serve in the Department of Conservation and the State Planning Office. Since 1987, he has been a consultant to wood products and paper companies, government agencies, and non-governmental organizations. He is the author of numerous publications, including The Northeast’s Changing Forests, published by the Harvard University Forest
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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