The sociometabolic transition of a small Greek island: Assessing stock dynamics, resource flows, and material circularity from 1929 to 2019
Bibliographic record
Abstract
Their geomorphological characteristics make island systems special focal points for sustainability challenges. The Circular Economy (CE) Action Plan of the European Union foresees tailored solution sets for Europe's outermost regions and islands to tackle region-specific sustainability challenges. We address the question of how islands can achieve more sustainable resource use by utilizing the socioeconomic metabolism (SEM) framework to assess and explore CE strategies for the Greek island of Samothraki. For this purpose, we apply material and energy flow analysis on a regional level and derive, as one of the first studies, a complete time series from 1929 to 2019 for socioeconomic biophysical stocks and flows according to mass-balance principles for an island economy. Results show that in the past 90 years Samothraki's material stocks grew fivefold, domestic material consumption threefold, and solid waste generation fivefold. Samothraki transitioned from an almost entirely circular biophysical economy toward one in which 40% of input materials and 30% of output materials are estimated as non-circular. This transition resulted in an accumulated solid waste stock on the island almost half the size of current material stocks in use. With this study we aim at providing ideas and opportunities for achieving more sustainable and circular material use on small islands. The published SEM database aims at supporting the public and the private sector and the island community at large with information key to establishing more sustainable material and energy use patterns on Samothraki. This article met the requirements for a Gold–Gold JIE data openness badge described at http://jie.click/badges.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".