Capacity utilization, factor substitution, and productivity growth in Canadian food processing sector
Bibliographic record
Abstract
Abstract The food processing industry has been confronted with unprecedented challenges as the costs of raw materials have risen rapidly, owing in part to the increased use of grains for ethanol. It is critical to comprehend how these trends affect the industry and potential coping techniques. This study estimates capacity utilization, which is a measurement that is well-suited to identify how input prices affect productivity in the short-run. The results show that capacity utilization decreased significantly after the year 2005 when raw materials input prices skyrocketed. TFP growth has also slowed significantly because of this. According to the estimated elasticities, the industry has little potential to deal with the cost challenge through factor substitution. Another conclusion is that capacity utilization has a positive elasticity with respect to the cost of raw materials. Because it is related to induced capital stock adjustment, which is only achievable in the long run, this is an indicator of how the industry will be affected in the long-run.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".