The Canada–United States productivity puzzle: regional evidence of the pulp and paper industry, 1971–2005
Bibliographic record
Abstract
We analyze the total factor productivity (TFP) of the pulp and paper industry in three Canadian provinces (British Columbia, Ontario, and Quebec) and in three United States (US) states that are contiguously located south of the border (Washington, Illinois, and Maine) over the period of 1971 to 2005. We find that the industry in the three Canadian provinces had much higher TFP growth rates in the era following the Free-Trade Agreement (FTA) signed in 1988. In terms of productivity level, this relative TFP surge allowed the industry in Ontario and British Columbia to move ahead of Illinois and Washington, respectively; however, Quebec trailed further Maine, which is the overall leader in the sample. Our results in this particular case reveal that the Canadian pulp and paper industry did not contribute to the overall Canada–US productivity gap.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| 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 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".