Ways to improve the professional competencies of logisticians in crisis minds
Bibliographic record
Abstract
1. Riggio R. E., Newstead T. Crisis leadership. Annual review of organizational psychology and organizational behavior. 2022. Vol. 10. pp. 201-224. https://doi.org/10.1146/annurev-orgpsych-120920-044838 \n2. Шатайло О. Кризи соціально-економічних систем: прояви та ознаки. Вісник Київського національного торговельно-економічного університету. 2019. Т. 124. № 2. С. 91-102. URL: https://journals.knute.edu.ua/scientia-fructuosa/issue/view/35 (дата звернення: 29.10.2024). 3. Компетентності менеджера з логістики промислового підприємства / Л. Ліпич та ін. 2021. Економічний часопис національного університету імені Лесі Українки. 2021. Т. 1, № 25. С. 119-128. https://doi.org/10.29038/2786-4618-2021-01-119-128 \n4. Online university teaching during and after the covid-19 crisis: refocusing teacher presence and learning activity / C. Rapanta et al. Postdigital science and education. 2020. Vol. 2, no. 3. p. 923–945. URL: https://doi.org/10.1007/s42438-020-00155-y \n5. Городянська Л. В. Роль цифрової компетентності фахівця у сфері кібербезпеки в умовах воєнних загроз. Формування компетентностей обдарованої особистості в системі позашкільної та вищої освіти : науковий журнал, Київ : НАУ, 2023. № 1. С. 210-217. https://doi.org/10.18372/2786-823.1.17497 \n6. Lee S.-H. Crisis classifications in mobility: Reporting the first COVID death in Taiwan. Discourse studies. 2024. https://doi.org/10.1177/14614456231219741 \n7. Ковцур К. Г., Любий Є. В. Сучасні затребувані компетенції логістів на ринку праці. Вища освіта за новими стандартами: виклики у контексті діджиталізації та інтеграції в міжнародний освітній простір : матеріали ІІ міжнар. наук.-метод. конф., 23 берез. 2023 р. Харків : Харків. нац. автомоб.-дор. ун-т., 2023. С. 75-77. URL: https://dspace.khadi.kharkov.ua/handle/123456789/17151 (дата звернення: 29.10.2024). \n8. Here’s how you can assess the essential skills and competencies of logistics professionals. LinkedIn. 2024. URL: https://www.linkedin.com/advice/1/heres-how-you-can-assess-essential-skills-lpbdf (date of access: 19.10.2024). \n9. Logistics 4.0 skills requirements: evidence from a developing country. Canadian journal of business and information studies. 2022. p. 24-36. https://doi.org/10.34104/cjbis.022.024036 \n10. Training of future logistics and supply chain managers: a competency approach / N. Zamkova et al. Financial and credit activity problems of theory and practice. 2023. Vol. 1, № 48. p. 427-440. https://doi.org/10.55643/fcaptp.1.48.2023.3946 \n11. The effect of collaboration and IT competency on reverse logistics competency - Evidence from Brazilian supply chain executives / E. A. R. de Campos et al. Environmental impact assessment review. 2020. Vol. 84. https://doi.org/10.1016/j.eiar.2020.106433
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.065 | 0.025 |
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".