How coupled is coupled human-natural systems research?
Bibliographic record
Abstract
Interdisciplinary research that links human and natural systems is critical to addressing complex environmental and ecological problems. A growing number of interdisciplinary research teams investigate coupled natural-human systems, but the degree to which they actually examine two-way linkages between the systems is limited. We examined aspects of interdisciplinary teams that were explicitly funded to conduct research including such linkages by considering attributes of team leaders, team members, and analysis methods employed. Our objective was to investigate the degree to which interdisciplinary teams studying coupled natural-human systems publish research that displays two-way linkages between systems. Our analysis shows that team members’ academic disciplines and the types of analysis methods that interdisciplinary teams apply play a crucial role in the success of the team in publishing articles that include two-way linkages. We found that the success of developing two-way linkages is enhanced when teams include leaders and/or members from interdisciplinary academic disciplines (e.g., planning departments, sustainability, environmental economics, biological and ecological engineering, and individuals affiliated with more than one academic department from different discipline categories). Additionally, the presence of social science members increases the likelihood of two-way linkages, whereas the presence of physical science or biological/life science members decreases this likelihood. Among articles that included two-way linkages, essentially all utilized a conceptual-/literature-review approach, or included simulation model analysis. Based on these findings, we conclude that interdisciplinary teams are not a mere sum of people from different academic disciplines, but a group of people who have the ability to incorporate different disciplines conceptually and analytically. To move forward, it is important to acknowledge that becoming an interdisciplinary researcher takes deliberative work. Educational programs that train students and early career scholars with flexible thinking and analytical capacities may be the key to furthering coupled natural-human systems research.
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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 | 0.071 | 0.213 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.019 | 0.029 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".