Feeding Europe, the Portuguese geoestrategic position and the logistic gains, opportunity for the next quarter
Bibliographic record
Abstract
People’s food is today divided in two main origins, fresh products and grains. The first group being the vegetables, legumes and fruits, also still the capture of wild fish from the sea waters, although fish farming production is already overlapping the wildcatch collection. So, presently, grains are directly or indirectly, the basis of meat, aquaculture fish, milk, eggs, cheese, bread, pastas, and almost all processed food products. The main food grains are the commodities largely traded in world like maze, wheat or barley. These food commodities produced and consumed in different parts of the globe, travel in big vessels. An opportunity is then identified that can make intercontinental grain logistics more efficient, particularly the one that serves Europe. The research work of the thesis is clearly composed by two preliminary tasks, the data analysis job to show the southern movement of the production of food commodities in the world globe; the other part, the collection of in-depth interviews of leaders in industry, related to food logistics, food commodities trading and ports, to discuss whether in Europe this change should appoint other port infrastructures improvement, for better supply-chain efficiency and regional development. In addition, a comparative case study analysis is considered for the discussion. Food is a vital element for humanity existence, in modern age, food become mass produced and transported around all the globe, looking for the best productivity, searching ideal clime, soils and water. Heavy logistics and international trade, made food travel thousands of kilometers to reach our plate on the opposite corner of the globe. Today large volumes of resources are dedicated for food production, transformation and distribution, so a vast quota of world global economy is taken by food business. Research and literature about these subjects is immense, difficult to classify as per relevance for use. A preliminary data analysis of the subject was proposed, a large volume of data was collected, for a second phase study being proposed to treat far larger data volumes, to trim and give consistence to the validation of the hypothesis previously formulated. The second phase of the research work, is a qualitative work of informant in-depth interviews conducted with 13 leaders in the industry. The sample represented a broad spectrum of leaders from across the EU, America, and especially Portugal. We must recognize that a qualitative approach may be intensive, complex, expensive and time consuming, but it is rich in details and revealing in new ways to explain a complex future vision of such research questions. Finally, using a case study methodology, a similar parallel phenomena is discussed to be added to the prospective framework emerged.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".