The Greening of the warehousing industry in Ontario : an analytical study of the extent of present day environmental sustainability programs
Bibliographic record
Abstract
The purpose of the paper is to explore the extent to which the Ontario warehousing industry has embraced environmental sustainability within its business strategy. This will provide a needed baseline on the current state of practice in the Province. This could also lay the foundation for future work in Ontario, particularly with respect to where improvements can be made. Data was collected through a review of Leonard’s Guide, a content analysis of publicly available information, and a survey of warehousing companies in Ontario. Multiple methods of collecting data were utilized for triangulation and to protect against the possibility not enough data would be available by one alone. The findings indicate that there have been some inroads made in implementing environmental sustainability programs within the warehousing industry of Ontario, but there is still room for improvement. The findings also indicate that third-party logistics (3PL) are more likely than warehousing/distribution companies to implement environmental sustainability programs, as are companies which had their trade areas beyond the borders of Canada.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".