Towards Understanding and Sustaining Natural Resource Systems through the Systems Perspective: A Systematic Evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A bibliometric and network analysis was performed to explore global research publication trends and to investigate relevant policy recommendations in the field of sustainability of natural resources, system dynamics, and systems thinking, to solve water resources issues and enhance water resource management. Overall, 1674 academic research articles data were generated from the Web of Science and Scopus databases, from 1981 to 2019. The findings of this study revealed that system dynamics and systems thinking research has significantly increased over the last decade (from 40 to 250 articles). Countries such as the USA (20%), China (18%), the United Kingdom (5%), Canada, Iran, Australia, and India (4% each) have the most publications and strongest collaborative networks. Sterman (2000) and Forrester (1961) had the most co-cited research while Zhang X had the highest citations, respectively. Results also showed that system theory which includes systems thinking and system dynamics were the most used keywords. The Journal of Cleaner Production was found to have published the highest number of systems thinking and system dynamics related studies, perhaps due to scope relevance. Despite the exponential rise in natural resource sustainability research globally, the result of this study shows that developing countries especially in Africa have low numbers of research publications in the field. Thus, the result of this study serves as a signal for policymakers to increase attention on research publications that could enhance natural resource sustainability, particularly in less developed countries in Africa where the application of systems thinking to natural resource management is limited.
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.
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 | 0.019 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it