Dynamic cost allocation in horizontal collaboration – a case study in forest transportation in Québec
Why this work is in the frame
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Bibliographic record
Abstract
Horizontal collaboration has emerged as a pivotal strategy in modern supply chain management, offering potential savings and improved efficiencies. However, unforeseen events often disrupt the streamlined operation of such collaborations, necessitating robust mechanisms for dynamic cost and benefit allocation. This paper proposes a dynamic approach that allocates benefits or costs based on the reasons behind the disruptions. The approach is based on adapted, well-known, equitable allocation principles. Through detailed analysis and case studies from the forest industry, we demonstrate how our proposed approach ensures fairness and adaptability, fostering stronger and more resilient collaborative relationships among stakeholders. The findings underscore the significance of adaptive allocation methods in promoting sustained collaboration, even when facing unforeseen challenges.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it