A Longitudinal Study of Water Recycling in Canadian Manufacturing Plants
Bibliographic record
Abstract
Industrial water use is an important part of most developed economies' total water use and one which is differentiated from other sectors' water use by the prevalence of recycling. Previous research applied to cross sectional surveys has identified the role of input prices and the scale of plant operations in determining the volume of water recirculated. We, on the other hand, employ longitudinal data to investigate the frequency of recirculation (that is, whether manufacturing plants recirculate or not). Our analysis of the data from several cross sections from Canada's Industrial Water Survey data shows that, while there are a number of pants that either never or always recirculate water, there is a sizable minority of plants who at times are observed to be recirculating and at other times are observed not to be recirculating. In order to investigate these phenomena, we construct a 'pseudo-panel' of data (Deaton, 1985) and estimate a fixed effects model of recycling frequency. Our estimation model provides insights into industrial water recycling. In particular, the scale of plant operations is not found to be significant in explaining the likelihood of recirculation while water-related input prices are significant.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".