Structural and Environmental Performance of Evolving Industrial Symbiosis: A Multidimensional Analysis
Bibliographic record
Abstract
Industrial symbiosis (IS) involves networks of organizations collaborating through flow exchanges. Scientific research has shown that such systems are able to provide benefits at the environmental level. Structural organization and stability were also studied, as they are linked to resilience (maintenance of activity over time), especially with ecological network analysis (ENA), which considers several dimensions in the assessment of a network organization. Studies combining ENA and environmental assessment are lacking in the literature; therefore, the links between the two dimensions are not well documented. The intention of this study was to fill this gap by analyzing structural and environmental performance simultaneously using ENA and a life-cycle-analysis-based approach focusing on the structural topology of IS. The results show that the two dimensions do not strictly influence each other. Structural performance was found to vary depending on the network structure topology, whereas environmental performance was influenced by the network complexity. To ensure the continuation of IS benefits, the two dimensions should be considered in the decision-making process in IS planification, even if they are independent evaluation criteria. Tradeoffs should be based on IS development possibilities and territorial needs.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 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".