Streamlining humanitarian and peacekeeping supply chains
Bibliographic record
Abstract
Purpose – Over the last decade, temporary supply chains (TSCs) have become a well-recognized logistics model. In TSCs, supply chain members are organized for an ad hoc project; they pool resources in order to make the project successful. Although it might be perceived that TSCs are unstable due to their temporary nature, this paper aims to discuss how TSCs can be managed so as to be both stable and agile, while achieving the stated objectives; since the stability-agility context could be really challenging in humanitarian and peacekeeping supply chains, this is the one that has been selected. Design/methodology/approach – The authors reviewed the literature, research reports and electronic documents on humanitarian and peacekeeping supply chains, to understand the main challenges in terms of managerial and social impacts of logistical operations in a disaster context. Findings – The disaster context is very peculiar, since it requires tremendous agility when a natural or man-made catastrophe hits, so that as many lives as possible can be saved and that the situation could get back rapidly to a relatively normal level. The paper shows that TSCs require an advanced level of time and organizational stability of the human and material resources involved in order to be highly flexible. In other words, an efficient TSC relies on “anticipated responsiveness”, a major managerial challenge in the years to come. Originality/value – The paper clarifies the management of humanitarian and peacekeeping supply chains and identifies the importance of anticipation capability to improve logistical responsiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".