Open and Closed Black Soldier Fly Systems Tradeoff Analysis
Bibliographic record
Abstract
When it comes to waste management, it is essential to consider human and environmental safety, financial feasibility, and social benefits. So often, one of these factors takes priority over the others. However, integrated social, environmental, and economic benefits are more apparent with insect-based waste treatment technology like the Black Soldier Fly (BSF) system. BSF waste treatment is an innovative and adaptable technique that offers sustainable benefits to communities in developing countries because it can be designed to be as simple or complex as required. Depending on the local context, simple (open) systems based on naturally occurring flies or more complex (closed) systems based on captured fly colonies are viable. However, what are the environmental tradeoffs when choosing between these two systems? The surge in the use of both BSF systems makes this consideration imperative. Furthermore, until now, the environmental and social impacts of open BSF waste treatment systems have not been compared. The environmental tradeoffs in implementing an affordable, socially accepted, open BSF biowaste treatment system are explored in this study to address this gap. Co-production for delivering public services was used to develop an accepted BSF system through a case study by applying qualitative interaction research methodologies. A Life Cycle Assessment (LCA) was then used to compare the environmental impacts of natural ovipositing BSF systems compared to captured BSF systems. Natural ovipositing BSF (open) systems, in comparison, have reduced climate change (33%) and water, land, and energy use (55%, 37% and 32%) while also motivating the development of socially accepted infrastructure measured through community engagement. This mixed-methods approach facilitates the development of contextually appropriate technology in low-income communities in developing and developed countries while also reducing environmental consequences.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".