World Class Supply Chain 2022: Creating a Sustainable Future
Bibliographic record
Abstract
The Sixth Annual World Class Supply Chain Summit on May 4th, 2022 was a landmark in at least threes ways: First, it marked a return to having the annual summit in-person following the COVID-driven cancellation of the 2020 summit and the virtual delivery format of the 2021 summit. Second, the 2022 summit’s hybrid format (simultaneous in-person delivery in Milton, Ontario and online delivery to delegates who attended virtually) required the summit planning team to creatively deploy teleconferencing tools that characterise the pandemic-era. Third, for the very first time, we scheduled a Student Forum segment in which students presented material from their immersive experience with supply chain issues that two Canadian organizations grappled with. This innovative Student Forum, like the panel of executives, and the keynote presentation, yielded thought-provoking perspectives on the summit theme: Creating a Sustainable Future.\nThe panel discussion emphasized five key issues related to supply chain sustainability, the Student Forum addressed issues relevant to established manufacturer as well as start-up manufacturers, and the keynote presentation focused on post-pandemic supply chains. Across the extensive range of topics that these speakers covered during their formal delivery and their less formal but scheduled "fireside chats" with the audience, three topics took the lion’s share of the dialogue:\n(i) Sustainability touches a very broad range of a company’s internal and external activities\n(ii) The transition from a company’s current position to its desired position is very unlikely to be straightforward and direct\n(iii) Companies need to be more proactive in identifying, recruiting, and nurturing new talent for supply chains of the future\nThe importance of not only considering what has happened and/or is happening in supply chains but also what could happen in the future was featured throughout the day’s dialogue and was evidently epitomized in the title of Professor Alan Amling’s keynote address: Post-pandemic SCM Practices, Insights, and Predictions. Some notable future supply chain items in his presentation include natural resource scarcity, population growth, demographic shifts, and man-made supply chain disruptions. These are among the insights that will be explicated in this white paper.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
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".